Determination of meningioma brain tumour grades using Raman microspectroscopy imaging

Raman microspectroscopy imaging was used to distinguish 90 brain tissue samples into meningiomas Grade I and Grade II.

Spectrochemical differentiation of meningioma tumours based on attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy

Meningiomas are the commonest types of tumours in the central nervous system (CNS). It is a benign type of tumour divided into three WHO grades (I, II and III) associated with tumour growth rate and likelihood of recurrence, where surgical outcomes and patient treatments are dependent on the meningioma grade and histological subtype. The development of alternative approaches based on attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy could aid meningioma grade determination and its biospectrochemical profiling in an automated fashion. Herein, ATR-FTIR in combination with chemometric techniques is employed to distinguish grade I, grade II and grade I meningiomas that re-occurred. Ninety-nine patients were investigated in this study where their formalin-fixed paraffin-embedded (FFPE) brain tissue samples were analysed by ATR-FTIR spectroscopy. Subsequent classification was performed via principal component analysis plus linear discriminant analysis (PCA-LDA) and partial least squares plus discriminant analysis (PLS-DA). PLS-DA gave the best results where grade I and grade II meningiomas were discriminated with 79% accuracy, 80% sensitivity and 73% specificity, while grade I versus grade I recurrence and grade II versus grade I recurrence were discriminated with 94% accuracy (94% sensitivity and specificity) and 97% accuracy (97% sensitivity and 100% specificity), respectively. Several wavenumbers were identified as possible biomarkers towards tumour differentiation. The majority of these were associated with lipids, protein, DNA/RNA and carbohydrate alterations. These findings demonstrate the potential of ATR-FTIR spectroscopy towards meningioma grade discrimination as a fast, low-cost, non-destructive and sensitive tool for clinical settings.

Graphical abstract

Paediatric meningiomas: a multi-centre case series of 27 patients

PURPOSE

This study presents a series of paediatric meningiomas and discusses aetiology, risk factors and outcomes with comparison to current literature.

METHODS

This is a retrospective review of surgically treated paediatric meningiomas from three UK centres: the University Hospital of Wales, Alder Hey Children's Hospital and Royal Manchester Children's Hospital. Twenty-seven patients aged 16 and under at the time of their first procedure were identified over a 15-year period (1 January 2007 and 1 March 2023). Electronic medical records were used to collect data on age at presentation, sex, location of tumour(s), extent of resection, histology, WHO grade, complications, outcomes and associated conditions, notably neurofibromatosis type 2 (NF2).

RESULTS

Twenty-seven patients underwent 39 procedures. There were 13 males and 14 females. The median age was 13 years (range, 8 months to 16 years). Twenty-one (75%) were WHO grade 1, 6 (21%) were grade 2 and 1 (4%) was grade 3. Eight patients (30%) had confirmed NF2. Twelve patients (44%) were sporadic cases. Twenty-five percent and 50% were the recurrence rate in WHO grade 1 and 2 tumours, respectively.

CONCLUSION

The risk of grade 1 tumour recurrence was higher than within the adult population. This may be due to histological features of paediatric meningiomas differing from the adult population, and therefore, the WHO grading system may not be reflective of recurrence risk. Future molecular profiling and larger studies are required given the rarity of these cases.

Predicting meningioma recurrence using spectrochemical analysis of tissues and subsequent predictive computational algorithms

Introduction

Meningioma recurrence remains a clinical dilemma. This has a significant clinical and huge financial implication. Hence, the search for predictors for meningioma recurrence has become an increasingly urgent research topic in recent years.

Objective

Using spectrochemical analytical methods such as attenuated total reflection Fourier-transform infrared (ATR-FTIR) and Raman spectroscopy, our primary objective is to compare the spectral fingerprint signature of WHO grade I meningioma vs. WHO grade I meningioma that recurred. Secondary objectives compare WHO grade I meningioma vs. WHO grade II meningioma and WHO grade II meningioma vs. WHO grade I meningioma recurrence.

Materials and Methods

Our selection criteria included convexity meningioma only restricted to Simpson grade I & II only and WHO grade I & grade II only with a minimum 5 years follow up. We obtained tissue from tumour blocks retrieved from the tissue bank. These were sectioned onto slides and de-waxed prior to ATR-FTIR or Raman spectrochemical analysis. Derived spectral datasets were then explored for discriminating features using computational algorithms in the IRootLab toolbox within MATLAB; this allowed for classification and feature extraction.

Results

After analysing the data using various classification algorithms with cross-validation to avoid over-fitting of the spectral data, we can readily and blindly segregate those meningioma samples that recurred from those that did not recur in the follow-up timeframe. The forward feature extraction classification algorithms generated results that exhibited excellent sensitivity and specificity, especially with spectra obtained following ATR-FTIR spectroscopy. Our secondary objectives remain to be fully developed.

Raman hyperspectral imaging coupled to three-dimensional discriminant analysis: Classification of meningiomas brain tumour grades

Meningiomas remains a clinical dilemma. They are the commonest "benign" types of brain tumours and, although being typically benign, they are divided into three WHO grades categories (I, II and III) which are associated with the tumour growth rate and likelihood of recurrence. Recurrence depends on extend of surgery as well as histopathological diagnosis. There is a marked variation amongst surgeons in the follow-up arrangements for their patients even within the same unit which has a significant clinical, and financial implication. Knowing the tumour grade rapidly is an important factor to predict surgical outcomes and adequate patient treatment. Clinical follow up sometimes is haphazard and not based on clear evidence. Spectrochemical techniques are a powerful tool for cancer diagnostics. Raman hyperspectral imaging is able to generate spatially-distributed spectrochemical signatures with great sensitivity. Using this technique, 95 brain tissue samples (66 meningiomas WHO grade I, 24 meningiomas WHO grade II and 5 meningiomas that reoccurred) were analysed in order to discriminate grade I and grade II samples. Newly-developed three-dimensional discriminant analysis algorithms were used to process the hyperspectral imaging data in a 3D fashion. Three-dimensional principal component analysis quadratic discriminant analysis (3D-PCA-QDA) was able to distinguish grade I and grade II meningioma samples with 96% test accuracy (100% sensitivity and 95% specificity). This technique is here shown to be a high-throughput, reagent-free, non-destructive, and can give accurate predictive information regarding the meningioma tumour grade, hence, having enormous clinical potential with regards to being developed for intra-operative real-time assessment of disease.

Determination of meningioma brain tissue grades using Raman hyperspectral imaging

Raman spectroscopy is a powerful tool used to analyse biological materials, where spectral biomarkers such as proteins (1500–1700 cm-1), carbohydrates (470–1200 cm-1) and phosphate groups of DNA (980, 1080–1240 cm-1) can be detected. A major advantage is that it is reagent-free and unaffected by water interference, which is ideal for biological applications. Raman hyperspectral imaging combines the chemical sensitivity of this spectrochemical technique with spatially distributed information. Herein, Raman microspectroscopy imaging (50 × 50 μm tissue area, 50× magnification, 50% laser power, 0.1 ms exposure time, 780–1858 cm-1 spectral range) was used to investigate 79 brain tissue samples (sourced from the Brain Tumour North West) in order to differentiate meningioma Grade I (n=55) versus Grade II (n=24). Meningioma is the commonest type of brain tumour with the majority of them being benign tumours (Grade I) whilst a few are aggressive or malignant (Grade II). Grade II tumours have a poor prognosis by their nature, hence new sensitive diagnostic tools are essential. Using partial least squares discriminant analysis (PLS-DA) with 20 LVs (99% explained variance), we were able to differentiate Grade I versus Grade II meningioma with a classification accuracy of 99% in an internal validation set of 23 samples (16 Grade I, seven Grade II); this was with an accuracy of 85% for an external test set of similar size. These findings highlight the potential of Raman hyperspectral imaging for differentiation of meningioma tumours.