Extra-axial brain tumors

Contrast-enhanced CT rim sign may predict vestibular schwannoma adhesion and postoperative complications

AIM

To investigate the clinical and radiological features to predict adhesion between vestibular schwannoma (VS) and brain tissue which is a critical risk factor for postoperative infarction and residual tumour.

MATERIAL AND METHODS

One hundred and seven consecutive VS surgeries were analysed. After excluding cases without contrast-enhanced (CE) computed tomography (CT), Koos grades 1 and 2, and cases with incomplete clinical data, 44 patients were finally included in the study. Enhancement of the tumour capsule on the brainstem side on CE-CT was defined as the CE-CT rim sign, which was analysed along with clinical characteristics, including tumour adhesion and postoperative complications.

RESULTS

Eight patients exhibited CE-CT rim signs; 17 had tumour adhesions. Four patients had postoperative infarction at the ipsilateral middle cerebellar peduncle; 18 exhibited postoperative infarction and/or residual tumour at the middle cerebellar peduncle. The CE-CT rim sign significantly correlated with tumour adhesion, postoperative infarction, and postoperative infarction and/or residual tumour in the cerebellar peduncle. Univariate regression analysis revealed that the CE-CT rim sign significantly correlated with tumour adhesion (odds ratio [OR] 6.81, 95% confidence interval [CI] 1.18-39.25, p=0.032) and postoperative infarction and/or residual tumour at the cerebellar peduncle (OR 6.00, 95% CI 1.04-34.31, p=0.044).

CONCLUSION

The CE-CT rim sign was identified in 18.2% of patients with VS and significantly correlated with tumour adhesion and postoperative complications, such as postoperative infarction and residual tumour. This study highlights the importance of the preoperative CE-CT rim sign in VS, which is predictive of tumour adhesion and postoperative complications.

Anatomical variations of foramen of the diaphragma sellae and neighboring structures: a cadaveric study

The aim of our study was to examine the variations and types of foramen of diaphragma sellae (FDS) and their relationship with nearby surgical landmarks on cadavers.Twenty adult (9 male, 11 female) formalin-fixed cadaveric heads were bilaterally used to analyze the anatomical relationships around the supradiaphragmatic region of sella turcica. Lengths and distances of nearby surgical landmarks were measured by a digital microcaliper. SPSS version 25 was used to analyze the comparison between genders and body sides. Dorsum sellae distances to tuberculum sellae and the optic chiasm(OC) were higher in males than females (p < 0.05). Type 8 infundibulum passage was the most common variation with 50%. There was no finding related to types 1-4 of infundibulum passage. Thus, the present study has indicated that the infundibulum passes mostly from the posterior half of the foramen. The shape of the foramen was irregular in 45%, circular in 20%, sagittally oval in 20%, and horizontally oval in 15% of the cases. The OC was noted normal in 60%, prefixed in 35%, and postfixed in 5% of the cases. Comprehensive anatomical knowledge about the types of the FDS and their neighboring structures is crucial for preoperative planning of sellar region diseases in terms of navigating the region when accessing the foramen. Discrimination of variations of FDS, OC, and pituitary stalk, their relationships, and differences between genders is useful to minimize potential surgical complications.

Imaging biomarkers associated with extra-axial intracranial tumors: a systematic review

Extra-axial brain tumors are extra-cerebral tumors and are usually benign. The choice of treatment for extra-axial tumors is often dependent on the growth of the tumor, and imaging plays a significant role in monitoring growth and clinical decision-making. This motivates the investigation of imaging biomarkers for these tumors that may be incorporated into clinical workflows to inform treatment decisions. The databases from Pubmed, Web of Science, Embase, and Medline were searched from 1 January 2000 to 7 March 2022, to systematically identify relevant publications in this area. All studies that used an imaging tool and found an association with a growth-related factor, including molecular markers, grade, survival, growth/progression, recurrence, and treatment outcomes, were included in this review. We included 42 studies, comprising 22 studies (50%) of patients with meningioma; 17 studies (38.6%) of patients with pituitary tumors; three studies (6.8%) of patients with vestibular schwannomas; and two studies (4.5%) of patients with solitary fibrous tumors. The included studies were explicitly and narratively analyzed according to tumor type and imaging tool. The risk of bias and concerns regarding applicability were assessed using QUADAS-2. Most studies (41/44) used statistics-based analysis methods, and a small number of studies (3/44) used machine learning. Our review highlights an opportunity for future work to focus on machine learning-based deep feature identification as biomarkers, combining various feature classes such as size, shape, and intensity. Systematic Review Registration: PROSPERO, CRD42022306922.

Large Middle Cranial Fossa Schwannoma: A Rare Presentation of Vestibular Schwannoma

Schwannomas are benign tumors composed of neoplastic Schwann cells and rarely occur in the central nervous system. Schwannomas account for approximately 8% of intracranial tumors and most commonly originate from cranial nerve VIII at the cerebellopontine angle in the posterior fossa. Herein, we report two cases of vestibular schwannomas extending in the middle fossa. The first case shows a 51-year-old male who presented with a history of mild headaches for one year associated with acute nausea, vomiting, and word-finding difficulties. Imaging revealed a large multicystic contrast-enhancing lesion in the left middle cranial fossa. The middle fossa lesion was resected with pathology indicating a schwannoma. The second case shows a 63-year-old woman who presented with seizures, right-sided hearing loss, and right-sided facial weakness. On MRI, she is found to have a large right middle fossa lesion originating from the right internal auditory canal and consistent with vestibular schwannoma with a 9 mm leftward midline shift. The histopathologic examination of the excised tumor indicated a schwannoma. Schwannomas most commonly occur in the posterior fossa when they present intracranially. However, in rare occurrences, they may present as middle fossa masses with significant intracranial compression.

Preoperative Assessment and Prediction of Consistency of Intracranial Meningioma Utilizing the Apparent Diffusion Coefficient Values

Objectives Consistency of meningioma is important for preoperative planning, surgical resection, and predicting surgical outcomes. We prospectively evaluated the utility of the apparent diffusion coefficient (ADC) values to assess the consistency of meningioma.

Methods Preoperative magnetic resonance imaging (MRI) was performed on 23 patients with meningioma before undergoing surgical resection and the average/mean of ADC minimum (ADCmin), maximum (ADCmax), and mean (ADCmean) values were calculated. Intraoperatively, the meningiomas were characterized as firm or soft and correlated with ADC values.

Results ADCmin, ADCmax, and ADCmean values of soft and firm meningiomas were significantly different with a p-value of < 0.05. ADCmin value of < 691.3 × 10−6 mm2/s had 80% sensitivity and 84.6% specificity for identifying firm from the soft tumors with the area under the curve (AUC) = 0.862, p-value of 0.004, positive predictive value (PPV) 80, and negative predictive value (NPV) 84.6. ADCmax value of < 933.6 × 10−6 mm2/s had 70% sensitivity and 84.6% specificity for identifying firm from the soft tumors with AUC = 0.823, p-value of 0.009, PPV 77.8, and NPV 78.6. ADCmean value of < 840.8 × 10−6 mm2/s had 90% sensitivity and 76.9% specificity for identifying firm from the soft tumors with AUC = 0.900, p-value of 0.001, PPV 75, and NPV 90.9.

Conclusion Diffusion-weighted MRI using ADC minimum, ADC maximum, and ADC mean values can be used to differentiate firm from soft meningiomas. Meningiomas with hard consistency showed relatively low ADC values.

Incidence, Clinicopathological Profile and Location - Based Outcome of Intracranial Meningiomas: 10-Year Institutional Study with Review of Literature

Intracranial meningiomas are the most common extra-axial tumors, representing 15% of all brain tumors. Arising from the arachnoid cells, and common in middle-aged women, 90% meningiomas are benign. We conducted a 10-year study on 183 cases of intracranial meningiomas and observed a lower and decreasing trend; the mean age was 43.3 years but there was also a significant incidence in young females. Parasagittal/falx (29%), sphenoid ridge, convexity meningiomas and middle cranial fossa locations were more common. Histopathologically, meningothelial meningioma was the most common. Benign (WHO I) tumors were found in above 90%, atypical (WHO II) in 5% cases, and malignant (WHO III) in < 4% patients. Most patients underwent Simpsons Grade I excision (35.6%) with dural reconstruction because of late presentations. Posterior fossa meningiomas were mostly benign, while intraventricular ones were mostly malignant with highest postoperation mortality. Mortality in operated patients was 9.8% but was highest in anterior fossa tumors (12.5%).

Precise discrimination between meningiomas and schwannomas using time-to-signal intensity curves and percentage signal recoveries obtained from dynamic susceptibility perfusion imaging

BACKGROUND AND PURPOSE

Meningiomas and schwannomas are common extra-axial brain tumors. Discrimination is challenging in some locations when characteristic imaging features are absent. This study investigated the accuracy of percentage signal recoveries obtained from dynamic susceptibility contrast perfusion imaging (DSC-PI) in discriminating meningiomas and schwannomas.

MATERIAL AND METHODS

Retrospective database research was conducted. Sixty nine meningioma and 15 schwannoma having DSC-PI between January 2016 and February 2020 were included. Time to signal intensity curves (TSIC) were analyzed and grouped as T1-dominant leakage, T2*-dominant leakage and return to baseline. Relative cerebral blood volume (rCBV), relative mean transit time (rMTT), percentage signal recovery 1 (PSR 1) and PSR 2 values were calculated. The differences between the groups were investigated. Receiver operating characteristic curves were operated.

RESULTS

rCBV, rMTT, PSR 1 and PSR 2 values were statistically different between meningiomas and schwannomas. PSR 2 provided the best discrimination. With the cut off value of 1.08 for PSR 2, meningiomas and schwannomas were differentiated with 95.7% sensitivity and 93.3% specificity. TSICs were also different between two groups. Most of meningiomas showed T2*-dominant leakage (78.2%), whereas most of shwannomas showed T1-dominant leakage (93.3%).

CONCLUSION

DSC-PI is a useful imaging tool for non-invasive discrimination of meningiomas and schwannomas. Particularly, percentage signal recoveries discriminates meningiomas and schwannomas with high sensitivity and specificity.

[Modern standards for magnetic resonance imaging of the brain tumors]

Neuroimaging is essential in survey of patients with brain tumors. An important objectives of neuroimaging are highly reliable non-invasive diagnosis, treatment planning and evaluation of treatment outcomes. Magnetic resonance imaging (MRI) is one of the modern neuroimaging methods. This technique ensures analysis of structural cerebral changes, vascular and metabolic characteristics of brain tumors. It is necessary to standardize imaging parameters and unify protocols and methods considering a widespread use of MRI for brain tumors. In our practice, we use our own experience, world literature data and evidence-based international guidelines on the diagnosis of various brain diseases. The purpose of this review is to study the modern principles of magnetic resonance imaging in adults with brain tumors in neurosurgical practice.

A deep learning radiomics model for preoperative grading in meningioma

OBJECTIVES

To noninvasively differentiate meningioma grades by deep learning radiomics (DLR) model based on routine post-contrast MRI.

METHODS

We enrolled 181 patients with histopathologic diagnosis of meningioma who received post-contrast MRI preoperative examinations from 2 hospitals (99 in the primary cohort and 82 in the validation cohort). All the tumors were segmented based on post-contrast axial T1 weighted images (T1WI), from which 2048 deep learning features were extracted by the convolutional neural network. The random forest algorithm was used to select features with importance values over 0.001, upon which a deep learning signature was built by a linear discriminant analysis classifier. The performance of our DLR model was assessed by discrimination and calibration in the independent validation cohort. For comparison, a radiomic model based on hand-crafted features and a fusion model were built.

RESULTS

The DLR signature comprised 39 deep learning features and showed good discrimination performance in both the primary and validation cohorts. The area under curve (AUC), sensitivity, and specificity for predicting meningioma grades were 0.811(95% CI, 0.635-0.986), 0.769, and 0.898 respectively in the validation cohort. DLR performance was superior over the hand-crafted features. Calibration curves of DLR model showed good agreements between the prediction probability and the observed outcome of high-grade meningioma.

CONCLUSIONS

Using routine MRI data, we developed a DLR model with good performance for noninvasively individualized prediction of meningioma grades, which achieved a quantization capability superior over the hand-crafted features. This model has potential to guide and facilitate the clinical decision-making of whether to observe or to treat patients by providing prognostic information.

Guidelines for radiographic imaging of cranial neuropathies

Disruption of the complex pathways of the 12 cranial nerves can occur at any site along their course, and many, varied pathologic processes may initially manifest as dysfunction and neuropathy. Radiographic imaging (computed topography or magnetic resonance imaging) is frequently used to evaluate cranial neuropathies; however, indications for imaging and imaging method of choice vary considerably between the cranial nerves. The purpose of this review is to provide an analysis of the diagnostic yield and the most clinically appropriate means to evaluate cranial neuropathies using radiographic imaging. Using the PubMed MEDLINE NCBI database, a total of 49,079 articles' results were retrieved on September 20, 2014. Scholarly articles that discuss the etiology, incidence, and use of imaging in the context of evaluation and diagnostic yield of the 12 cranial nerves were evaluated for the purposes of this review. We combined primary research, guidelines, and best practice recommendations to create a practical framework for the radiographic evaluation of cranial neuropathies.

Current Clinical Brain Tumor Imaging

Neuroimaging plays an ever evolving role in the diagnosis, treatment planning, and post-therapy assessment of brain tumors. This review provides an overview of current magnetic resonance imaging (MRI) methods routinely employed in the care of the brain tumor patient. Specifically, we focus on advanced techniques including diffusion, perfusion, spectroscopy, tractography, and functional MRI as they pertain to noninvasive characterization of brain tumors and pretreatment evaluation. The utility of both structural and physiological MRI in the post-therapeutic brain evaluation is also reviewed with special attention to the challenges presented by pseudoprogression and pseudoresponse.

[Extra-axial tumors of the central nervous system]

Extra-axial tumors are intracranial neoplasms but are not located within the brain parenchyma. The localization of intracranial neoplasms helps to narrow down the possible differential diagnoses and also plays a deciding role in the treatment strategy and the prognosis. For this reason exact localization of these lesions is extremely important. Extra-axial tumors are the most common neoplasms among adults. They can be divided in a broad spectrum of histopathological subgroups. The most common extra-axial tumors are meningiomas, which arise from the dura mater. In the vast majority of cases they are benign and slowly growing. Only a few rare subgroups show aggressive behavior.

Radiologic and histologic features of the T2 hyperintensity rim of meningiomas on magnetic resonance images

A hyperintensity rim is often seen at the brain-tumor interface of meningiomas upon T2-weighted (T2WI) magnetic resonance imaging (MRI), and it is referred to as the cerebrospinal fluid (CSF) space; however, the true nature of the rim remains unclear. We surveyed the MRI findings and the histopathologic characteristics of such rims. Our study population consisted of 53 consecutive patients who underwent meningioma removal at our hospital. The intensity of the rim on MRI scans obtained with different imaging sequences was assessed in all patients. We used 22 tumors for histopathologic investigation: tissue samples were acquired from both the tumor surface and from a deep intratumoral site. Of the 53 meningiomas, 37 (69.8%) manifested a hyperintensity rim on T2WI (T2-rim). The other 16 showed neither a hyperintense nor a hypointense rim on their T2WI. An enhancement effect corresponding to the rim was observed in 28 of the 37 (75.7%) T2-rim positive tumors. While 9 among the 37 tumors with a T2-rim (24.3%) did not show rim enhancement, they showed low intensity on fluid-attenuated inversion recovery (FLAIR) images. The microvascular density in the tumor capsule was significantly greater in the 12 T2-rim and rim enhancement positive tumors than in 10 tumors that were T2-rim negative or T2-rim positive, but rim enhancement-negative ( p < 0.001, Mann-Whitney U test). We found that 75.7% of T2 hyperintense rims that were detected at the brain-meningioma interface reflected a microvascular-rich capsule layer, rather than the CSF space.

Extra-axial brain tumors

Extra-axial brain tumors are the most common adult intracranial neoplasms and encompass a broad spectrum of pathologic subtypes. Meningiomas are the most common extra-axial brain tumor (approximately one-third of all intracranial neoplasms) and typically present as slowly growing dural-based masses. Benign meningiomas are very common, and may occasionally be difficult to differentiate from more aggressive subtypes (i.e., atypical or malignant varieties) or other dural-based masses with more aggressive biologic behavior (e.g., hemangiopericytoma or dural-based metastases). Many neoplasms that typically affect the brain parenchyma (intra-axial), such as gliomas, may also present with primary or secondary extra-axial involvement. This chapter provides a general and concise overview of the common types of extra-axial tumors and their typical imaging features.

Usefulness of dual-energy computed tomography imaging in the differential diagnosis of sellar meningiomas and pituitary adenomas: preliminary report

Objective

To quantitatively assess the imaging characteristics of sellar lesion in dual-energy computed tomography (CT) imaging for differentiation of sellar meningiomas and pituitary adenomas during the arterial phase (AP) and venous phase (VP).

Materials and Methods

51 patients with sellar/parasellar tumors (33 macroadenomas and 18 meningiomas) were examined with CT spectral imaging during the AP and the VP. Iodine concentrations were derived from iodine-based material-decomposition CT images and normalized to the iodine concentration in the aorta. The difference in Normalized iodine concentrations (NICs), HU curve slope (λHU), and mean CT values of lesions between the AP and VP were calculated. The two-sample t test was performed to compare quantitative parameters between sellar meningiomas and pituitary adenomas.

Results

NICs, λHU, and mean CT values in patients with sellar meningiomas differed significantly from those in patients with pituitary adenomas: Mean NICs were 43.52 mg/mL±1.35 versus 9.23 mg/mL ±2.44, respectively, during the AP and 52.13 mg/mL ±1.04 versus 24.37 mg/mL ±2.23 respectively, during the VP. λHU were −3.03±3.42 versus −0.53±0.23, respectively, during the AP and −2.96±0.41 versus −0.47±0.25, respectively, during the VP. Mean CT values were 193.63±2.08 versus 63.98±2.85, respectively, during the AP and 203.98±0.18 versus 77.66±0.91, respectively, during the VP. The combination of NIC and Mean CT value during VP had highest sensitivity (90.9%) and specificity (100%) among all phases.

Conclusion

Quantitative dual-energy CT imaging has promising potential for diagnostic differentiation of sellar meningiomas and pituitary adenomas.

Intracranial metastases: spectrum of MR imaging findings

Intracranial metastatic lesions arise through a number of routes. Therefore, they can involve any part of the central nervous system and their imaging appearances vary. Magnetic resonance imaging (MRI) plays a key role in lesion detection, lesion delineation, and differentiation of metastases from other intracranial disease processes. This article is a reasoned pictorial review illustrating the many faces of intracranial metastatic lesions based on the location - intra-axial metastases, calvarial metastases, dural metastases, leptomeningeal metastases, secondary invasion of the meninges by metastatic disease involving the calvarium and skull base, direct or perineural intracranial extension of head and neck neoplasm, and other unusual manifestations of intracranial metastases. We also review the role of advanced MRI to distinguish metastases from high-grade gliomas, tumor-mimicking lesions such as brain abscesses, and delayed post-radiation changes in radiosurgically treated patients.

[Extra-axial brain tumors]

Neuroradiology plays a key role in the diagnosis of patients with brain tumors. Computed tomography (CT) and especially magnetic resonance imaging (MRI) allow accurate anatomic depiction of intracerebral lesions. The implementation of native and contrast studies allows the characterization of the various lesions. This review discusses the imaging aspects with CT and MRI of the most common primary extra-axial brain tumors.

The A61G EGF polymorphism is associated with development of extraaxial nervous system tumors but not with overall survival

Epidermal growth factor can activate several signaling pathways, leading to proliferation, differentiation, and tumorigenesis of epithelial tissues by binding with its receptor. The EGF protein is involved in nervous system development, and polymorphisms in the EGF gene on chromosome band 4q25 are associated with brain cancers. The purpose of this study was to investigate the association between the single-nucleotide polymorphism of EGF+61G/A and extraaxial brain tumors in a population of the southeast of Brazil. We analyzed the genotype distribution of this polymorphism in 90 patients and 100 healthy subjects, using the polymerase chain reaction-restriction fragment length polymorphism technique. Comparison of genotype distribution revealed a significant difference between patients and control subjects (P < 0.001). The variant genotypes of A/G and G/G were associated with a significant increase of the risk of tumor development, compared with the homozygote A/A (P < 0.0001). When the analyses were stratified, we observed that the genotype G/G was more frequent in female patients (P=0.021). The same genotype was observed more frequently in patients with low-grade tumors (P=0.001). Overall survival rates did not show statistically significant differences. Our data suggest that the EGF A61G polymorphism can be associated with susceptibility to development of these tumors.

Intracranial lipomas: a retrospective study

Between 1996 and 2006, 17 patients with intracranial lipomas underwent MR imaging examination. Of these, two patients also had CT examination. Lipoma is not a typical tumor and could instead be called intracranial lipoma hamartoma or cerebral malformation. The predominant localization of the lipomas was close to midline structures, such as the area around the corpus callosum, quadrigeminal cisterns, etc. Interpreting the MRI it is necessary to differentiate epidermoid, dermoid and hemorrhage in the metahemoglobin stage from lipoma. Clinically, 47% of patients complained of headache, two presented with epileptic seizures and the remainder had different symptoms. The lipoma was just an incidental finding not related to the clinical symptomatology.