Pediatric high grade gliomas: A comprehensive histopathological, immunohistochemical and molecular integrated approach in routine practice.

Pediatric high grade gliomas have undergone remarkable changes in recent time with discovery of new molecular pathways. They have been added separately in current WHO 2021 blue book. All the entities show characteristic morphology and immunohistochemistry. Methylation data correctly identifies these entities into particular group of clusters. The pediatric group high grade glioma comprises- Diffuse midline glioma, H3K27-altered; Diffuse hemispheric glioma, H3G34-mutant; Diffuse pediatric-type high-grade glioma, H3-wild type & IDH-wild type; Infant hemispheric glioma and Epithelioid glioblastoma/Grade 3 pleomorphic xanthoastrocytoma and very rare IDH-mutant astrocytoma. However it is not always feasible to perform these molecular tests where cost-effective diagnosis is a major concern. Here we discuss the major entities with their characteristic histopathology, immunohistochemistry and molecular findings that may help to reach to suggest the diagnosis and help the clinician for appropriate treatment strategies. We have also made a simple algorithmic flow chart integrated with histopathology, immunohistochemistry and molecular characteristics for better understanding.

Potential Efficacy of 68 Ga-Trivehexin PET/CT and Immunohistochemical Validation of αvß6 Integrin Expression in Patients With Head and Neck Squamous Cell Carcinoma and Pancreatic Ductal Adenocarcinoma.

PURPOSE: αvß6 integrin is exclusively expressed in epithelial cells and is upregulated in many carcinomas, such as pancreatic ductal adenocarcinomas (PDACs) and head and neck squamous cell carcinomas (H&NSCCs). Trivehexin is a recently synthesized trimerized αvß6 integrin selective nonapeptide, which can be labeled with a positron emitter like 68 Ga. This is a pilot study to assess the potential role of 68 Ga-Trivehexin PET/CT in patients with H&NSCC and PDAC and their correlation with αvß6 integrin expression by the tumor tissue on immunohistochemistry (IHC). PATIENTS AND METHODS: Thirty-two patients with suspected H&NSCC (n = 20) or PDAC (n = 12) underwent whole-body 68 Ga-Trivehexin PET/CT and 18 F-FDG PET/CT scans on 2 separate days. All 32 patients underwent biopsy from the tumor site for histopathological diagnosis and IHC for αvß6 integrin expression. The degree of αvß6 integrin expression on IHC was scored using the immunoreactive score and modified 4-point immunoreactive score classification. RESULTS: The 68 Ga-Trivehexin PET images demonstrated increased tracer uptake (mean SUV max 5.9 ± 3.3) in the primary and metastatic lesions with good lesion delineation in 8 out of the 9 cases of PDACs. However, FDG PET showed increased tracer uptake in 7 cases (6.2 ± 2.6). Among various cases of H&NSCC, increased uptakes of 68 Ga-Trivehexin (6.6 ± 4.5) and 18 F-FDG (12.7 ± 6.7) were seen in 17 out of the 18 patients. The 2 cases of inflammatory changes with suspected disease recurrence showed increased tracer uptake in 18 F-FDG PET (7.98 ± 3.1) and no significant uptake in 68 Ga-Trivehexin PET (2.2 ± 0.34).IHC showed higher expression of αvß6 integrins in lesions with higher uptake of 68 Ga-Trivehexin. A higher sensitivity, specificity, and accuracy of 68 Ga-Trivehexin PET over 18 F-FDG PET was seen for detection of primary and metastatic lesions. CONCLUSIONS: 68 Ga-Trivehexin is a promising noninvasive molecular imaging agent for tumors expressing αvß6 integrin, especially in cases where 18 F-FDG PET/CT scan may be suboptimal due to its low uptake, or due to its nonspecific uptake around tumor sites.

Spinal astroblastoma, MN1 altered in 3-year-old child: An uncommon tumor at an unusual site.

Astroblastoma is an uncommon circumscribed glial tumor mostly involving the cerebral hemisphere. The characteristic molecular alteration is meningioma (disrupted in balanced translocation) 1 (MN1) rearrangement. No definite World Health Organization grade has been assigned as both low- and high-grade tumors are known to occur. Tumors in the spine are extremely rare; to date only three cases have been reported in the literature. A vigilant microscopy and ancillary testing aid in diagnosis when the tumors present in unusual locations, as in our case. The prompt differentiation of this tumor from its mimickers is a mandate as modalities of management are different and not clearly established.

Quantification of Radiomics features of Peritumoral Vasogenic Edema extracted from fluid-attenuated inversion recovery images in glioblastoma and isolated brain metastasis, using T1-dynamic contrast-enhanced Perfusion analysis.

The peritumoral vasogenic edema (PVE) in brain tumors exhibits varied characteristics. Brain metastasis (BM) and meningioma barely have tumor cells in PVE, while glioblastoma (GB) show tumor cell infiltration in most subjects. The purpose of this study was to investigate the PVE of these three pathologies using radiomics features in FLAIR images, with the hypothesis that the tumor cells might influence textural variation. Ex vivo experimentation of radiomics analysis of T1-weighted images of the culture medium with and without suspended tumor cells was also attempted to infer the possible influence of increasing tumor cells on radiomics features. This retrospective study involved magnetic resonance (MR) images acquired using a 3.0-T MR machine from 83 patients with 48 GB, 21 BM, and 14 meningioma. The 93 radiomics features were extracted from each subject's PVE mask from three pathologies using T1-dynamic contrast-enhanced MR imaging. Statistically significant (< 0.05, independent samples T-test) features were considered. Features maps were also computed for qualitative investigation. The same was carried out for T1-weighted cell line images but group comparison was carried out using one-way analysis of variance. Further, a random forest (RF)-based machine learning model was designed to classify the PVE of GB and BM. Texture-based variations, especially higher nonuniformity values, were observed in the PVE of GB. No significance was observed between BM and meningioma PVE. In cell line images, the culture medium had higher nonuniformity and was considerably reduced with increasing cell densities in four features. The RF model implemented with highly significant features provided improved area under the curve results. The possible infiltrative tumor cells in the PVE of the GB are likely influencing the texture values and are higher in comparison with BM PVE and may be of value in the differentiation of solitary metastasis from GB. However, the robustness of the features needs to be investigated with a larger cohort and across different scanners in the future.

Differentiation of Pilocytic Astrocytoma from Glioblastoma using a Machine-Learning framework based upon quantitative T1 perfusion MRI.

BACKGROUND AND PURPOSE: Differentiation of pilocytic astrocytoma (PA) from glioblastoma is difficult using conventional MRI parameters. The purpose of this study was to differentiate these two similar in appearance tumors using quantitative T1 perfusion MRI parameters combined under a machine learning framework. MATERIALS AND METHODS: This retrospective study included age/sex and location matched 26 PA and 33 glioblastoma patients with tumor histopathological characterization performed using WHO 2016 classification. Multi-parametric MRI data were acquired at 3 T scanner and included T1 perfusion and DWI data along with conventional MRI images. Analysis of T1 perfusion data using a leaky-tracer-kinetic-model, first-pass-model and piecewise-linear-model resulted in multiple quantitative parameters. ADC maps were also computed from DWI data. Tumors were segmented into sub-components such as enhancing and non-enhancing regions, edema and necrotic/cystic regions using T1 perfusion parameters. Enhancing and non-enhancing regions were combined and used as an ROI. A support-vector-machine classifier was developed for the classification of PA versus glioblastoma using T1 perfusion MRI parameters/features. The feature set was optimized using a random-forest based algorithm. Classification was also performed between the two tumor types using the ADC parameter. RESULTS: T1 perfusion parameter values were significantly different between the two groups. The combination of T1 perfusion parameters classified tumors more accurately with a cross validated error of 9.80% against that of ADC's 17.65% error. CONCLUSION: The approach of using quantitative T1 perfusion parameters based upon a support-vector-machine classifier reliably differentiated PA from glioblastoma and performed better classification than ADC.

Radiomics-based evaluation and possible characterization of dynamic contrast enhanced (DCE) perfusion derived different sub-regions of Glioblastoma.

BACKGROUND: Glioblastoma (GB) is among the most devastative brain tumors, which usually comprises sub-regions like enhancing tumor (ET), non-enhancing tumor (NET), edema (ED), and necrosis (NEC) as described on MRI. Semi-automated algorithms to extract these tumor subpart volumes and boundaries have been demonstrated using dynamic contrast-enhanced (DCE) perfusion imaging. We aim to characterize these sub-regions derived from DCE perfusion MRI using routine 3D post-contrast-T1 (T1GD) and FLAIR images with the aid of Radiomics analysis. We also explored the possibility of separating edema from tumor sub-regions by extracting the most influential radiomics features. METHODS: A total of 89 patients with histopathological confirmed IDH wild type GB were considered, who underwent the MR imaging with DCE perfusion-MRI. Perfusion and kinetic indices were computed and further used to segment tumor sub-regions. Radiomics features were extracted from FLAIR and T1GD images with PyRadiomics tool. Statistical analysis of the features was carried out using two approaches as well as machine learning (ML) models were constructed separately, i) within different tumor sub-regions and ii) ED as one category and the remaining sub-regions combined as another category. ML based predictive feature maps was also constructed. RESULTS: Seven features found to be statistically significant to differentiate tumor sub-regions in FLAIR and T1GD images, with p-value < 0.05 and AUC values in the range of 0.72 to 0.93. However, the edema features stood out in the analysis. In the second approach, the ML model was able to categorize the ED from the rest of the tumor sub-regions in FLAIR and T1GD images with AUC of 0.95 and 0.89 respectively. CONCLUSION: Radiomics-based specific feature values and maps help to characterize different tumor sub-regions. However, the GLDM_DependenceNonUniformity feature appears to be most specific for separating edema from the remaining tumor sub-regions using conventional FLAIR images. This may be of value in the segmentation of edema from tumors using conventional MRI in the future.

Role of intra-tumoral vasculature imaging features on susceptibility weighted imaging in differentiating primary central nervous system lymphoma from glioblastoma: a multiparametric comparison with pathological validation.

PURPOSE: Primary objective of this study was to retrospectively evaluate the potential of a range of qualitative and quantitative multiparametric features assessed on T2, post-contrast T1, DWI, DCE-MRI, and susceptibility-weighted-imaging (SWI) in differentiating evenly sampled cohort of primary-central-nervous-system-lymphoma (PCNSL) vs glioblastoma (GB) with pathological validation. METHODS: The study included MRI-data of histopathologically confirmed ninety-five GB and PCNSL patients scanned at 3.0 T MRI. A total of six qualitative features (three from T2 and post-contrast T1, three from SWI: thin-linear-uninterrupted-intra-tumoral-vasculature, broken-intra-tumoral-microvasculature, hemorrhage) were analyzed by three independent radiologists. Ten quantitative features from DWI and DCE-MRI were computed using in-house-developed algorithms. For qualitative features, Cohen's Kappa-interrater-variability-analysis was performed. Z-test and independent t-tests were performed to find significant qualitative and quantitative features respectively. Logistic-regression (LR) classifiers were implemented for evaluating performance of individual and various combinations of features in differentiating PCNSL vs GB. Performance evaluation was done via ROC-analysis. Pathological validation was performed to verify disintegration of vessel walls in GB and rim of viable neoplastic lymphoid cells with angiocentric-pattern in PCNSL. RESULTS: Three qualitative SWI features and four quantitative DCE-MRI features (rCBVcorr, Kep, Ve, and necrosis-volume-percentage) were significantly different (p < 0.05) between PCNSL and GB. Best diagnostic performance was observed with LR classifier using SWI features (AUC-0.99). The inclusion of quantitative features with SWI feature did not improve the differentiation accuracy. CONCLUSIONS: The combination of three qualitative SWI features using LR provided the highest accuracy in differentiating PCNSL and GB. Thin-linear-uninterrupted-intra-tumoral-vasculature in PCNSL and broken-intra-tumoral-microvasculature with hemorrhage in GB are the major contributors to the differentiation.

Medulloblastoma outcomes in tertiary care set-up in India using contemporary treatment protocols - A retrospective study.

Background: Medulloblastoma is the commonest embryonal brain tumor in children. It has shown improved outcomes with combined modality treatment. We aimed to study patient characteristics and survival outcomes of patients with this disease across two tertiary care centers in India. Methods: We analyzed data of patients with histological diagnosis of medulloblastoma treated from January 2010 to January 2016. Patient characteristics and follow-up data were retrieved from hospital records. Descriptive statistics were used to describe clinical and pathological characteristics. Overall survival (OS) was calculated from date of diagnosis to death due to any cause. Relapse-free survival (RFS) was calculated from date of diagnosis to occurrence of relapse or death. Result: Out of 26 patients treated, 24 were children and 2 were adults. Median age was 10 years (range = 0.8-22 years). Twenty (76.9%) patients were male. Fifteen (57.7%) patients were stratified as high-risk (HR), rest 11 (42.3%) were categorized as average risk (AR). Histopathology showed classical variety in majority of patients except for 4 (15%) cases, 3 with desmoplastic and 1 with anaplastic subtype. Median follow-up was 49.7 months (range= 4.2-102.5 months). Overall, eight (30.8%) patients relapsed and six (23%) deaths occurred. Five (33.3%) patients in HR category and 3 (27.3%) patients in AR group showed relapse. Median RFS and OS were not yet reached. Five-year RFS was 69.2% whereas five-year OS was 76.9%. Conclusion: This study highlighted patient characteristics and treatment outcomes in Indian patients. With adherence to standard treatment, high remission rates and improvement in mortality rates were achieved.

A Rare Case of Isolated Intraventricular Primary Central Nervous System Lymphoma in an 85-Year-Old Man.

Primary CNS lymphoma (PCNSL) is rare malignant B cell lymphoid tumor of brain which predominantly occurs in supratentorial region in periventricular location. Majority of PCNSL are of DLBCL type and idiopathic in etiology. Here we are reporting a case of primary CNS lymphoma, DLBCL involving extremely uncommon intraventricular location. Central neurocytoma, subependymal giant cell astrocytoma, choroid plexus tumors and meningiomas are the common diagnosis at this site. Aim of reporting this case is to bring awareness of unusual intraventricular location of primary CNS lymphoma which should be kept in mind before considering gross total excision of lesion.

Radial EBUS-Guided Cryobiopsy of Peripheral Lung Lesions With Flexible Bronchoscopy Without Using Guide-Sheath.

BACKGROUND: A guide-sheath (GS) is conventionally used as a conduit for biopsy forceps under the guidance of radial endobronchial ultrasound (REBUS) for sampling the peripheral pulmonary lesions (PPLs). As compared with forceps, the cryoprobe has the advantage of obtaining larger samples. There is a paucity of literature on the use of cryobiopsy for PPL. We evaluated the diagnostic yield and safety of the REBUS-guided cryobiopsy (REBUS-CB) without using GS for the diagnosis of PPL. METHODS: We retrospectively analyzed the database of 126 patients with PPL between November 2015 and December 2019. The REBUS-CB was performed using a flexible bronchoscopy without GS. Multidisciplinary consensus diagnostic yield was determined and procedural complications were recorded. RESULTS: The histopathologic diagnosis by REBUS-CB, which is the primary objective of the study was obtained in 99 (78.6%) of total 126 cases. Yield was significantly higher in central lesions as compared to adjacent lesions visualized by the REBUS probe (81.4% versus 53.8%, P=0.021) but not significantly different between large (≥30 mm) and small (<30 mm) lesions (81.6% versus 71.8%, P=0.214). The average largest diameter of biopsy specimens was 6.9 mm (range 1-12, SD 2.132). We witnessed moderate bleeding in 7 (5.6%) and post procedure hypoxic respiratory failure in 4 (3.2%) cases which could be managed without escalation of care. CONCLUSION: The REBUS-CB from peripheral lung lesions are feasible even without using GS and significantly large samples can be obtained.

Safety and diagnostic yield of transbronchial lung cryobiopsy by flexible bronchoscopy using laryngeal mask airway in diffuse and localized peripheral lung diseases: A single-center retrospective analysis of 326 cases.

BACKGROUND: Intubation with either an endotracheal tube or a rigid bronchoscope is generally preferred to provide airway protection as well as to manage unpredictable complications during transbronchial lung cryobiopsy (TBLC). The laryngeal mask airway has been described as a safe and convenient tool for airway control during bronchoscopy. AIMS AND OBJECTIVES: In this study, we evaluated the safety and outcome of using a laryngeal mask airway (LMA) as a conduit for performing TBLC by flexible video bronchoscopy (FB). METHODS: We retrospectively analyzed the database of the patients who underwent TBLC between November 2015 and September 2019. The procedure was performed using FB through LMA under general anesthesia. Prophylactic occlusion balloon was routinely used starting January 2017 onwards. Radial endobronchial ultrasound (R-EBUS) guidance was used for TBLC in the localized lung lesions when deemed necessary. Multidisciplinary consensus diagnostic yield was determined and periprocedural complications were recorded. RESULTS: A total of 326 patients were analysed. The overall diagnostic yield was 81.60% (266/326) which included a positive yield of 82.98% (161/194) in patients with diffuse lung disease and 79.54% (105/132) in patients with localized disease. Serious bleeding complication occurred in 3 (0.92%) cases. Pneumothorax was encountered in 8 (2.45%) cases. A total of 9 (2.76%) cases had at least 1 major complication. CONCLUSION: This study demonstrates that the use of LMA during TBLC by flexible bronchoscopy allows for a convenient port of entry, adequate airway support and effective endoscopic management of intrabronchial haemorrhage especially with the use of occlusion balloon.

Comparative evaluation of intracranial oligodendroglioma and astrocytoma of similar grades using conventional and T1-weighted DCE-MRI.

PURPOSE: This retrospective study was performed on a 3T MRI to determine the unique conventional MR imaging and T1-weighted DCE-MRI features of oligodendroglioma and astrocytoma and investigate the utility of machine learning algorithms in their differentiation. METHODS: Histologically confirmed, 81 treatment-naïve patients were classified into two groups as per WHO 2016 classification: oligodendroglioma (n = 16; grade II, n = 25; grade III) and astrocytoma (n = 10; grade II, n = 30; grade III). The differences in tumor morphology characteristics were evaluated using Z-test. T1-weighted DCE-MRI data were analyzed using an in-house built MATLAB program. The mean 90th percentile of relative cerebral blood flow, relative cerebral blood volume corrected, volume transfer rate from plasma to extracellular extravascular space, and extravascular extracellular space volume values were evaluated using independent Student's t test. Support vector machine (SVM) classifier was constructed to differentiate two groups across grade II, grade III, and grade II+III based on statistically significant features. RESULTS: Z-test signified only calcification among conventional MR features to categorize oligodendroglioma and astrocytoma across grade III and grade II+III tumors. No statistical significance was found in the perfusion parameters between two groups and its subtypes. SVM trained on calcification also provided moderate accuracy to differentiate oligodendroglioma from astrocytoma. CONCLUSION: We conclude that conventional MR features except calcification and the quantitative T1-weighted DCE-MRI parameters fail to discriminate between oligodendroglioma and astrocytoma. The SVM could not further aid in their differentiation. The study also suggests that the presence of more than 50% T2-FLAIR mismatch may be considered as a more conclusive sign for differentiation of IDH mutant astrocytoma.

Intraspinal Degenerative Cyst Causing Compression Of Cervicomedullary Junction.

BACKGROUND: Intraspinal degenerative cysts in the cervical region are rare disorders that may cause myelopathy or radiculopathy. Most of the intraspinal degenerative cysts reported are extradural cysts. This case report includes the neuroimaging, intraoperative, pathologic, and postoperative findings obtained in a patient with a degenerative intradural cyst at the craniovertebral (CV) junction. CASE DESCRIPTION: We report a patient presenting with progressive spastic quadriparesis resulting from compressive myelopathy due to intradural degenerative cyst at the CV junction. Preoperative magnetic resonance imaging showed the intradural cyst at the cervicomedullary junction with degenerative changes causing myelopathy. We performed decompression of the CV junction, and histopathology of the cyst revealed degenerative cyst. Postoperatively the symptoms were relieved with no apparent complication. Intraspinal degenerative cysts causing compressive myelopathy are rare. To the best of our knowledge, this is the first case of intradural degenerative cyst at the CV junction. CONCLUSIONS: In this case report, we demonstrated the clinical, imaging, intraoperative, and pathologic features of a degenerative intraspinal cyst at the CV junction that was intradural in location. Compression of the spinal cord resulted in a gradually progressive myelopathy that showed remarkable improvement immediately after decompression by cystectomy.

On differentiation between vasogenic edema and non-enhancing tumor in high-grade glioma patients using a support vector machine classifier based upon pre and post-surgery MRI images.

PURPOSE: High grade gliomas (HGGs) are infiltrative in nature. Differentiation between vasogenic edema and non-contrast enhancing tumor is difficult as both appear hyperintense in T2-W/FLAIR images. Most studies involving differentiation between vasogenic edema and non-enhancing tumor consider radiologist-based tumor delineation as the ground truth. However, analysis by a radiologist can be subjective and there remain both inter- and intra-rater differences. The objective of the current study is to develop a methodology for differentiation between non-enhancing tumor and vasogenic edema in HGG patients based on T1 perfusion MRI parameters, using a ground truth which is independent of a radiologist's manual delineation of the tumor. MATERIAL AND METHODS: This study included 9 HGG patients with pre- and post-surgery MRI data and 9 metastasis patients with pre-surgery MRI data. MRI data included conventional T1-W, T2-W, and FLAIR images and DCE-MRI dynamic images. In this study, the authors hypothesize that surgeried non-enhancing FLAIR hyperintense tissue, which was obtained using pre- and post-surgery MRI images of glioma patients, should be largely comprised of non-enhancing tumor. Hence this could be used as an alternative ground truth for the non-enhancing tumor region. Histological examination of the resected tissue was done for validation. Vasogenic edema was obtained from the non-enhancing FLAIR hyperintense region of metastasis patients, as they have a clear boundary between enhancing tumor and edema. DCE-MRI data analysis was performed to obtain T1 perfusion MRI parameters. Support Vector Machine (SVM) classification was performed using T1 perfusion MRI parameters to differentiate between non-enhancing tumor and vasogenic edema. Receiver-operating-characteristic (ROC) analysis was done on the results of the SVM classifier. For improved classification accuracy, the SVM output was post-processed via neighborhood smoothing. RESULTS: Histology results showed that resected tissue consists largely of tumorous tissue with 7.21 ±â€¯4.05% edema and a small amount of healthy tissue. SVM-based classification provided a misclassification error of 8.4% in differentiation between non-enhancing tumor and vasogenic edema, which was further reduced to 2.4% using neighborhood smoothing. CONCLUSION: The current study proposes a semiautomatic method for segmentation between non-enhancing tumor and vasogenic edema in HGG patients, based on an SVM classifier trained on an alternative ground truth to a radiologist's manual delineation of a tumor. The proposed methodology may prove to be a useful tool for pre- and post-operative evaluation of glioma patients.

Optical guiding-based cell focusing for Raman flow cell cytometer.

We report the use of an optical guiding arrangement generated in a microfluidic channel to produce a stream of single cells in a line for single-cell Raman spectroscopic analysis. The optical guiding arrangement consisted of dual-line optical tweezers, generated using a 1064 nm laser, aligned in the shape of a '' symbol. By controlling the laser power in the tweezers and the flow rate in the microfluidic channel, a single line flow of cells could be produced in the tail of the guiding arrangement, where the 514.5 nm Raman excitation beam was also located. Furthermore, by resonantly exciting the Raman spectrum, a good-quality Raman spectrum could be recorded from the flowing single cells as they passed through the Raman excitation focal spot without the need to trap the cells. As a proof of concept, it was shown that red blood cells (RBCs) could be guided to the tail of the optical guide and the Raman spectra of the resonantly excited cells could be recorded in a continuous manner without trapping the cells at a cell flow rate of ∼500 cells per h. From the recorded spectra, we were able to distinguish between RBCs containing hemoglobin in the normal form (normal-RBCs) and the met form (met-RBCs) from a mixture of RBCs comprising met-RBCs and normal-RBCs in a ratio of 1 : 9.

Neuropathology Education Using Social Media.

Social media use continues to grow among pathologists. Discussions of current topics, posts of educational information, and images of pathological entities are commonly found and distributed on popular sites such as Facebook and Twitter. However, little is known about the presence of neuropathology content in social media and the audience for such content. We designed and distributed a survey to assess the demographics of users viewing neuropathology content and their opinions about neuropathology in social media. User posts on the Facebook group, Surgical Neuropathology, were also analyzed. The results show that there is a demand for neuropathology content of high quality, curated by experts, and that this demand is present among both specialists and nonspecialists. These findings suggest that social media may be useful for rapid dissemination of information in the field of neuropathology. This format also offers a unique opportunity to extend the reach of information to nonneuropathologists who may not receive neuropathology journals or have access to specialty-level neuropathology training, to build networks between professionals, and potentially to influence public opinion of neuropathology on an international scale.

Advanced and amplified BOLD fluctuations in high-grade gliomas.

BACKGROUND: Glioma grade along with patient's age and general health are used for treatment planning and prognosis. PURPOSE: To characterize and quantify the spontaneous blood oxygen level-dependent (BOLD) fluctuations in gliomas using measures based on T2*-weighted signal time-series and to distinguish between high- and low-grade gliomas. STUDY TYPE: Retrospective. SUBJECTS: Twenty-one patients with high-grade and 13 patients with low-grade gliomas confirmed on histology were investigated. FIELD STRENGTH/SEQUENCE: Dynamic T2*-weighted (multislice single-shot echo-planar-imaging) magnetic resonance imaging (MRI) was performed on a 3T system with an 8-element receive-only head coil to measure the BOLD fluctuations. In addition, a dynamic T1 -weighted (3D fast field echo) dynamic contrast-enhanced (DCE) perfusion scan was performed. ASSESSMENT: Three BOLD measures were determined: the temporal shift (TS), amplitude of low frequency fluctuations (ALFF), and regional homogeneity (ReHo). DCE perfusion-based cerebral blood volume (CBV) and time-to-peak (TTP) maps were concurrently evaluated for comparison. STATISTICAL TESTS: An analysis-of-variance test was first used. When the test appeared significant, post-hoc analysis was performed using analysis-of-covariance with age as covariate. Logistic regression and receiver-operator characteristic curve analysis were also performed. RESULTS: TS was significantly advanced in high-grade gliomas compared to the contralateral cortex (P = 0.01) and low-grade gliomas (P = 0.009). In high-grade gliomas, ALFF and CBV were significantly higher than the contralateral cortex (P = 0.041 and P = 0.008, respectively) and low-grade gliomas (P = 0.036 and P = 0.01, respectively). ReHo and TTP did not show significant differences between high- and low-grade gliomas (P = 0.46 and P = 0.42, respectively). The area-under-curve was above 0.7 only for the TS, ALFF, and CBV measures. DATA CONCLUSION: Advanced and amplified hemodynamic fluctuations manifest in high-grade gliomas, but not in low-grade gliomas, and can be assessed using BOLD measures. Preliminary results showed that quantification of spontaneous fluctuations has potential for hemodynamic characterization of gliomas and distinguishing between high- and low-grade gliomas. LEVEL OF EVIDENCE: 4 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2018;47:1616-1625.