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

Early Surgery Prolongs Professional Activity in IDH Mutant Low-Grade Glioma Patients: A Policy Change Analysis

Background

Until 2015, Dutch guidelines recommended follow-up and biopsy rather than surgery as initial care for suspected low-grade gliomas (LGG). Given evidence that surgery could extend patient survival, our center stopped following this guideline on January 1, 2010 and opted for early maximal safe resection of LGG. The effects of early surgery on the ability of patients to work remains little documented.

Methods

A total of 104 patients operated on at our center between January 2000 and April 2013 and diagnosed with the WHO 2016 grade 2 astrocytoma, IDH mutant or oligodendroglioma, IDH mutant and deleted 1p19q were included. The clinical characteristics, survival, and work history of patients operated on before or after January 2010 were obtained from the patients' records and compared. The minimal follow-up was 8 years.

Results

As per policy change, the interval between radiological diagnosis and first surgery decreased significantly after 2010. Likewise, before 2010, 25.8% of tumors were initially biopsied, 51.6% were resected under anesthesia, and 22.5% under awake conditions versus 14.3%, 23.8%, and 61.9% after this date (p < 0.001). The severity of permanent postoperative neurological deficits decreased after 2010. In total, 82.5% of the patients returned to work postoperatively before 2010 versus 100% after 2010. The postoperative control of epilepsy increased significantly after 2010 (74.4% vs. 47.9%). The median time from diagnosis to a definitive incapacity to work increased by more than 2 years after 2010 (88.7 vs. 62.2 months).

Conclusion

A policy shift towards early aggressive surgical treatment of IDH mutant LGG is safe and prolongs the patients' ability to work.

Radiological evaluation of ex novo high grade glioma: velocity of diametric expansion and acceleration time study

Background

One of the greatest neuro-oncological concern remains the lack of knowledge about the etiopathogenesis and physiopathology of gliomas. Several studies reported a strict correlation between radiological features and biological behaviour of gliomas; in this way the velocity of diametric expansion (VDE) correlate with lower grade glioma aggressiveness. However, there are no the same strong evidences for high grade gliomas (HGG) because of the lack of several preoperative MRI.

Patients and methods

We describe a series of 4 patients affected by HGG followed from 2014 to January 2019. Two patients are male and two female; two had a pathological diagnosis of glioblastoma (GBM), one of anaplastic astrocytoma (AA) and one had a neuroradiological diagnosis of GBM. The VDE and the acceleration time (AT) was calculated for fluid attenuated inversion recovery (FLAIR) volume and for the enhancing nodule (EN). Every patients underwent sequential MRI study along a mean period of 413 days.

Results

Mean VDE evaluated on FLAIR volume was 39.91 mm/year. Mean percentage ratio between peak values and mean value of acceleration was 282.7%. Median appearance time of EN after first MRI scan was 432 days. Mean VDE was 45.02 mm/year. Mean percentage ratio between peak values and mean value of acceleration was 257.52%.

Conclusions

To our knowledge, this is the first report on VDE and acceleration growth in HGG confirming their strong aggressiveness. In a case in which we need to repeat an MRI, time between consecutive scans should be reduced to a maximum of 15–20 days and surgery should be executed as soon as possible.

Inter-rater agreement in glioma segmentations on longitudinal MRI

Background

Tumor segmentation of glioma on MRI is a technique to monitor, quantify and report disease progression. Manual MRI segmentation is the gold standard but very labor intensive. At present the quality of this gold standard is not known for different stages of the disease, and prior work has mainly focused on treatment-naive glioblastoma. In this paper we studied the inter-rater agreement of manual MRI segmentation of glioblastoma and WHO grade II-III glioma for novices and experts at three stages of disease. We also studied the impact of inter-observer variation on extent of resection and growth rate.

Methods

In 20 patients with WHO grade IV glioblastoma and 20 patients with WHO grade II-III glioma (defined as non-glioblastoma) both the enhancing and non-enhancing tumor elements were segmented on MRI, using specialized software, by four novices and four experts before surgery, after surgery and at time of tumor progression. We used the generalized conformity index (GCI) and the intra-class correlation coefficient (ICC) of tumor volume as main outcome measures for inter-rater agreement.

Results

For glioblastoma, segmentations by experts and novices were comparable. The inter-rater agreement of enhancing tumor elements was excellent before surgery (GCI 0.79, ICC 0.99) poor after surgery (GCI 0.32, ICC 0.92), and good at progression (GCI 0.65, ICC 0.91). For non-glioblastoma, the inter-rater agreement was generally higher between experts than between novices. The inter-rater agreement was excellent between experts before surgery (GCI 0.77, ICC 0.92), was reasonable after surgery (GCI 0.48, ICC 0.84), and good at progression (GCI 0.60, ICC 0.80). The inter-rater agreement was good between novices before surgery (GCI 0.66, ICC 0.73), was poor after surgery (GCI 0.33, ICC 0.55), and poor at progression (GCI 0.36, ICC 0.73). Further analysis showed that the lower inter-rater agreement of segmentation on postoperative MRI could only partly be explained by the smaller volumes and fragmentation of residual tumor. The median interquartile range of extent of resection between raters was 8.3% and of growth rate was 0.22 mm/year.

Conclusion

Manual tumor segmentations on MRI have reasonable agreement for use in spatial and volumetric analysis. Agreement in spatial overlap is of concern with segmentation after surgery for glioblastoma and with segmentation of non-glioblastoma by non-experts.

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Inter-rater agreement for longitudinal glioma segmentation was determined.

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Agreement between 4 experts was higher than between 4 novices.

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Three time-points of glioblastoma (WHO IV) and diffuse glioma (WHO II-III) are studied.

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Impact on extent of resection and growth rate measurements was determined.

A high 18F-FDOPA uptake is associated with a slow growth rate in diffuse Grade II-III gliomas

OBJECTIVE

In diffuse Grade II-III gliomas, a high 3,4-dihydroxy-6-(¹⁸F)-fluoro-L-phenylalanine (¹⁸F-FDOPA) positron emission tomography (PET) uptake, with a standardized uptake value (SUV_max)/contralateral brain tissue ratio greater than 1.8, was previously found to be consistently associated with the presence of an isocitrate dehydrogenase (IDH) mutation, whereas this mutation is typically associated with a better prognosis. This pilot study was aimed to ascertain the prognostic value of this high ¹⁸F-FDOPA uptake in diffuse Grade II-III gliomas with regard to the velocity of diameter expansion (VDE), which represents an established landmark of better prognosis when below 4 mm per year.

METHODS

20 patients (42 ± 10 years, 10 female) with newly-diagnosed diffuse Grade II-III gliomas (17 with IDH mutation) were retrospectively included. All had a ¹⁸F-FDOPA PET, quantified with SUV_max ratio, along with a serial MRI enabling VDE determination.

RESULTS

SUV_max ratio was above 1.8 in 5 patients (25%) all of whom had a VDE <4 mm/year (100%) and IDH mutation (100%). Moreover, a SUV_max ratio above 1.8 was associated with higher rates of VDE <4 mm/year in the overall population (45 vs 0%, p = 0.04) and also in the subgroup of patients with IDH mutation (45 vs 0%, p = 0.10).

CONCLUSION

This pilot study shows that in diffuse Grade II-III gliomas, a high ¹⁸F-FDOPA uptake would be predictive of low tumour growth, with a different prognostic significance than IDH mutation. Advances in knowledge: ¹⁸F-FDOPA PET in a single session imaging could have prognostic value in initial diagnosis of diffuse Grade II-III gliomas.

Natural history of de novo high grade glioma: first description of growth parabola

Etiopathogenesis and physiopathology of gliomas are largely unknown. Recently, many authors have proved a strict correlation between the velocity of diametric expansion (VDE) on the magnetic resonance imaging (MRI) and the biological behavior of these tumors, especially in low grade gliomas (LGGs). Unfortunately, natural history of High Grade Gliomas (HGGs) has not been well clarified because of its fast progression, late diagnoses and early surgical intervention. We describe, for the first time to our knowledge, the case of asymptomatic patient with an incidentally discovered de novo HGG with a total of 17 months of follow-up. A male patient was referred to our consultation for routinely follow-up after meningioma resection 5 years before. He underwent MRI every year without any neuroradiological alterations. A new MRI image presented a non-enhancing lesion in the right temporal lobe with 3.55 cm of mean tumor diameter (MTD) and 35.6 mm/year of VDE. After two months interval, the lesion had 3.97 cm of MTD and 27.8 mm/year of VDE. Although we have strongly suggested surgical resection, patient have delayed the operation for personal issues. After other 3 months, the tumor showed enhancement with 4.5 of MTD and 17.4 mm/year of VDE. We speculate that the descending parabola is due to initial mass effect and hypoxia of the tumor core. We also underline the crucial role of the VDE determining, in order to predict the nature of the lesion and address the most effective treatment for each patient.

A Patch-Based Approach for the Segmentation of Pathologies: Application to Glioma Labelling

In this paper, we describe a novel and generic approach to address fully-automatic segmentation of brain tumors by using multi-atlas patch-based voting techniques. In addition to avoiding the local search window assumption, the conventional patch-based framework is enhanced through several simple procedures: an improvement of the training dataset in terms of both label purity and intensity statistics, augmented features to implicitly guide the nearest-neighbor-search, multi-scale patches, invariance to cube isometries, stratification of the votes with respect to cases and labels. A probabilistic model automatically delineates regions of interest enclosing high-probability tumor volumes, which allows the algorithm to achieve highly competitive running time despite minimal processing power and resources. This method was evaluated on Multimodal Brain Tumor Image Segmentation challenge datasets. State-of-the-art results are achieved, with a limited learning stage thus restricting the risk of overfit. Moreover, segmentation smoothness does not involve any post-processing.