====== Low-Grade Glioma magnetic resonance imaging ======

Sometimes, the findings on the [[brain magnetic resonance imaging]] are sufficiently clear that [[low-grade glioma diagnosis]] is fairly certain. In such cases, a [[biopsy]] may not be necessary. However, in most cases, a [[biopsy]] is recommended to establish the type of tumor that is present.

{{::lowgradegliomamri.jpg|}}

A.- Homogeneous region of high [[signal intensity]] on [[T2]]/[[FLAIR]]-weighted images.

B.- Low signal intensity on [[T1]] precontrast images.

C.- Faint [[contrast enhancement]] on the T1 postcontrast images.

===== T2 =====

{{::lowgradegliomat2.png?200|}}

Extensive alteration of [[signal intensity]] in the [[temporal lobe]], [[limbic system]] [[region]], [[insula]] and lower region of the [[basal ganglia]] on the left side 

==== Case series ====


Preoperative MR images of 158 patients (discovery set = 112, external validation set = 46) with IDHwt lower-grade gliomas (WHO grade II or III) were retrospectively analyzed using the Visually Accessible Rembrandt Images feature set. Radiologic risk scores (RRSs) for overall survival were derived from the least absolute shrinkage and selection operator and elastic net. Multivariable Cox regression analysis, including age, Karnofsky Performance score, extent of resection, WHO grade, and RRS, was performed. The added prognostic value of RRS was calculated by comparing the integrated area under the receiver operating characteristic curve (iAUC) between models with and without RRS.

The presence of cysts, pial invasion, and cortical involvement were favorable prognostic factors, while ependymal extension, multifocal or multicentric distribution, nonlobar location, proportion of necrosis > 33%, satellites, and eloquent cortex involvement were significantly associated with worse prognosis. RRS independently predicted survival and significantly enhanced model performance for survival prediction when integrated to clinical features (iAUC increased to 0.773-0.777 from 0.737), which was successfully validated on the validation set (iAUC increased to 0.805-0.830 from 0.735).

MRI features associated with prognosis in patients with IDHwt lower-grade gliomas were identified. RRSs derived from MRI features independently predicted survival and significantly improved performance of survival prediction models when integrated into clinical features
((Park CJ, Han K, Shin H, Ahn SS, Choi YS, Park YW, Chang JH, Kim SH, Jain R,
Lee SK. MR image phenotypes may add prognostic value to clinical features in IDH 
wild-type lower-grade gliomas. Eur Radiol. 2020 Feb 14. doi:
10.1007/s00330-020-06683-2. [Epub ahead of print] PubMed PMID: 32060714.
)).
----
[[Calcification]]s may be evident as areas of [[T2]] [[hyperintensity]]/[[T1]] [[Hypointensity]] in up to 20% of [[lesion]]s, including [[oligodendroglioma]]s and [[astrocytoma]]s, and are particularly suggestive of oligodendrogliomas
((Pirzkall A, Nelson SJ, McKnight TR, Takahashi MM, Li X, Graves EE, Verhey LJ, 
Wara WW, Larson DA, Sneed PK. Metabolic imaging of low-grade gliomas with
three-dimensional magnetic resonance spectroscopy. Int J Radiat Oncol Biol Phys. 
2002 Aug 1;53(5):1254-64. PubMed PMID: 12128127.)).

Gliomas, in general, infiltrate the surrounding parenchyma despite apparent radiographic margins observed on T2/FLAIR sequences
((Pirzkall A, Nelson SJ, McKnight TR, Takahashi MM, Li X, Graves EE, Verhey LJ, 
Wara WW, Larson DA, Sneed PK. Metabolic imaging of low-grade gliomas with
three-dimensional magnetic resonance spectroscopy. Int J Radiat Oncol Biol Phys. 
2002 Aug 1;53(5):1254-64. PubMed PMID: 12128127.))
((van den Bent MJ, Wefel JS, Schiff D, Taphoorn MJ, Jaeckle K, Junck L,
Armstrong T, Choucair A, Waldman AD, Gorlia T, Chamberlain M, Baumert BG,
Vogelbaum MA, Macdonald DR, Reardon DA, Wen PY, Chang SM, Jacobs AH. Response
assessment in neuro-oncology (a report of the RANO group): assessment of outcome 
in trials of diffuse low-grade gliomas. Lancet Oncol. 2011 Jun;12(6):583-93. doi:
10.1016/S1470-2045(11)70057-2. Epub 2011 Apr 5. Review. PubMed PMID: 21474379.
)).

Contrast enhancement, if present, is minimal, and is more likely to be seen with oligodendrogliomas
((Pirzkall A, Nelson SJ, McKnight TR, Takahashi MM, Li X, Graves EE, Verhey LJ, 
Wara WW, Larson DA, Sneed PK. Metabolic imaging of low-grade gliomas with
three-dimensional magnetic resonance spectroscopy. Int J Radiat Oncol Biol Phys. 
2002 Aug 1;53(5):1254-64. PubMed PMID: 12128127.)).

Although contrast enhancement has been classically associated with a higher degree of malignancy, some degree of contrast enhancement may be seen in up to 60% of LGG
((Pouratian N, Asthagiri A, Jagannathan J, Shaffrey ME, Schiff D. Surgery
Insight: the role of surgery in the management of low-grade gliomas. Nat Clin
Pract Neurol. 2007 Nov;3(11):628-39. Review. PubMed PMID: 17982433.
)).

LGGs differ from grade III and IV gliomas, as the latter often demonstrate a higher degree of tumor heterogeneity and contrast enhancement, restricted diffusion on diffusion-weighted imaging magnetic resonance (MR) sequences, and increased relative cerebral blood volume on perfusion-weighted MRI
((Fan GG, Deng QL, Wu ZH, Guo QY. Usefulness of diffusion/perfusion-weighted MRI
in patients with non-enhancing supratentorial brain gliomas: a valuable tool to
predict tumour grading? Br J Radiol. 2006 Aug;79(944):652-8. Epub 2006 Apr 26.
PubMed PMID: 16641420.))
((Baehring JM, Bi WL, Bannykh S, Piepmeier JM, Fulbright RK. Diffusion MRI in
the early diagnosis of malignant glioma. J Neurooncol. 2007 Apr;82(2):221-5. Epub
2006 Oct 7. PubMed PMID: 17029014.
)).

----
Hwan-Ho Cho and Hyunjin Park, presented a method to predict the grades of [[Glioma]]s using [[Radiomic]]s imaging features. MICCAI Brain Tumor Segmentation Challenge (BRATs 2015) training data, its segmentation ground truth and the ground truth labels were used for this work. 45 radiomics features based on histogram, shape and gray-level co-occurrence matrix (GLCM) were extracted from each [[FLAIR]], [[T1]], T1-Contrast, [[T2]] image to quantify the property of Gliomas. Significant features among 180 features were selected through L1-norm regularization (LASSO). Based on LASSO coefficient and selected feature values, they computed a LASSO score and gliomas were classified into [[low-grade glioma]] (LGG) or high-grade glimoa (HGG) through logistic regression. Classification result was validated by a 10-fold cross validation. The method achieved accuracy of 0.8981, sensitivity of 0.8889, specificity of 0.9074, and area under the curve (AUC) = 0.8870
((Hwan-Ho Cho, Hyunjin Park. Classification of low-grade and high-grade glioma
using multi-modal image radiomics features. Conf Proc IEEE Eng Med Biol Soc. 2017
Jul;2017:3081-3084. doi: 10.1109/EMBC.2017.8037508. PubMed PMID: 29060549.
)).


----
[[Arterial spin labelled imaging]], [[DTI]], and [[Proton magnetic resonance spectroscopic imaging]] are useful for predicting glioma grade. Additionally, the parameters obtained on DTI and MR spectroscopy closely correlated with the proliferative potential of gliomas
((Fudaba H, Shimomura T, Abe T, Matsuta H, Momii Y, Sugita K, Ooba H, Kamida T, 
Hikawa T, Fujiki M. Comparison of Multiple Parameters Obtained on 3T Pulsed
Arterial Spin-Labeling, Diffusion Tensor Imaging, and MRS and the Ki-67 Labeling 
Index in Evaluating Glioma Grading. AJNR Am J Neuroradiol. 2014 Jul 3. [Epub
ahead of print] PubMed PMID: 24994829.
)).

The [[Apparent Diffusion Coefficient]] (ADC) values of low-grade (WHO I-II) glioma were higher than that of high-grade (WHO III-IV), but the cell density of low-grade glioma was apparently lower than that of high-grade glioma. The ADC values and density of tumor cells were negatively correlated with WHO malignant grades, while the density of cells of glioma was positively correlated with WHO malignant grades
((Chen SD, Hou PF, Lou L, Jin X, Wang TH, Xu JL. The correlation between MR
diffusion-weighted imaging and pathological grades on glioma. Eur Rev Med
Pharmacol Sci. 2014 Jul;18(13):1904-9. PubMed PMID: 25010621.
)).

Usually, [[low-grade glioma]]s show no increase in tumor rCBV, whereas [[high-grade glioma]]s demonstrate high [[relative cerebral blood volume]] (rCBV) that in some cases even extends outside the contrast-enhancing portions of the tumor
((Hu L. S. et al. Correlations between perfusion MR imaging cerebral blood volume, microvessel quantification, and clinical outcome using stereotactic analysis in recurrent high-grade glioma. AJNR Am J Neuroradiol 33, 69–76, 10.3174/ajnr.A2743 (2012).)).

Preoperative [[rCBV]] is one of the important prognostic factors significantly connected with survival
((Majchrzak K, Kaspera W, Bobek-Billewicz B, Hebda A, Stasik-Pres G, Majchrzak H, Ładziński P. The assessment of prognostic factors in surgical treatment of low-grade gliomas: a prospective study. Clin Neurol Neurosurg. 2012 Oct;114(8):1135-44. doi: 10.1016/j.clineuro.2012.02.054. Epub 2012 Mar 17. PubMed PMID: 22425370.)).