Peritumoral Edema Research Articles

319 Precision Medicine for Meningiomas: Machine Learning Using Radiomic Feature Analysis Identifies Ki-67 Proliferative Index as a Prognostic Marker of Clinical Outcomes

INTRODUCTION: An elevated Ki-67 is one crucial factor that influences meningioma behavior. Machine learning(ML) using radiomic feature analysis can identify phenotypic pixel-level imaging signatures for enhanced tumor diagnostics. METHODS: Radiomic feature extraction using least-absolute-shrinkage-and-selection-operator(LASSO) wrapped with support vector machine (SVM) through nested cross-validation is used to stratify tumors based on Ki-67 <5% and ≥5%. Clinical outcomes were evaluated based on the predictive power of this algorithm. RESULTS: 343 patients are included (WHO grade I:291, grade II:43, grade III:9). Overall mean follow-up time is 33.9 months (range: 0-105). The rate of recurrence is 14.4%, 44.2% and 77.8% for grade I, II, and III tumors, respectively. The mean Ki-67% for grade 1, 2 and 3 meningiomas is 4.79+/-3.87 (range: 0.3-33.6), 16.07+/-13.83 (range: 1.5-49), and 35.7+/-13.3 (range: 18-57.4), respectively (p = 0.03). However, there is no difference in tumor and peritumoral edema volumes between meningioma WHO grades 1-3. A total of 46 high-ranking radiomic features were selected to build a ML model. ROC curves for the ML algorithm reveals AUC’s of 0.83 [95% CI: 0.78-0.89] and 0.84 [0.75-0.94] for the discovery (N = 257) and validation (N = 86) cohort, respectively, for classifying Ki-67% based on a 5% cutoff, independent of WHO grade. Kaplan-Meier curves using the ML algorithm reveals decreased progression-free-survival (PFS) for predicted Ki-67 >5% (p < 0.001) for all tumors in the cohort, as well as in sub-analyses of non-skull base tumors (p < 0.001) and skull-base tumors (p < 0.001). A comparison of histopathological PFS versus ML-predicted outcomes based on Ki-67 reveals good concordance for grade I, II and III tumors. CONCLUSIONS: ML using radiomic feature analysis can be used to stratify meningiomas based on Ki-67 with excellent accuracy. The predictive power of this model reveals distinctly divergent PFS outcomes, and can be used to guide treatment strategy.

Factors associated with pre-operative and early and late post-operative seizures in patients with supratentorial meningiomas.

Risk factors for epilepsy in meningioma patients are not yet clearly defined, however, seizure freedom is a significant factor for quality of life after surgery. We performed a retrospective study of the 333 adult patients who received surgery for supratentorial meningioma at our centre. Various clinical, radiological, and surgical variables were included in the multivariate regression, and the outcomes measured were the occurrence of seizure(s) pre-operatively, during the hospitalization, and during the follow-up period. A total of 89 (26,7%) patients experienced pre-operative seizures, of whom 62.9% were seizure-free after the surgery. Of 244 patients without epilepsy before surgery, 11.9% had at least one seizure post-operatively. In total, 63 of our patients (18.9%) experienced seizures after the surgery, of whom 20 had refractory epilepsy. Multivariate analysis identified the following predictors of pre-operative seizures: absence of headache (OR: 0.23, CI: 2.55-8.50), the presence of significant peritumoural oedema (OR: 4.35, CI: 2.57-7.35), and younger age (OR: 0.97 per year increase, CI: 0.95-0.99). Factors associated with early post-operative seizures were: younger age (OR: 0.96 per year increase, CI: 0.93-0.99) and presence of pre-operative seizures (OR: 2.73, CI: 1.13-6.57), while the presence of pre-operative seizures (OR: 4.73, CI: 2,05-10.92), tumour progression (OR: 5.38, CI: 2.25-12.89) and neurological worsening (OR: 5.21 CI: 1.72-15.81) were significant for late post-operative seizures. Our results from a single-centre meningioma cohort confirm, in general, data from some previous studies regarding patients' characteristics for both pre-operative and overall post-operative epilepsy. Besides previously described risk factors, younger age was important for pre-operative and early post-operative seizures. Epilepsy is common in patients with recurrence of meningioma, but the variables of significance for refractory seizures in these patients require further examination.

The Performance of Different Machine Learning Algorithm and Regression Models in Predicting High-Grade Intracranial Meningioma

Meningioma is the most common primary tumor of the central nervous system (CNS). Individualized treatment strategies should be formulated for the patients according to the WHO (World Health Organization) grade. Our aim was to investigate the effectiveness of various machine learning and traditional statistical models in predicting the WHO grade of preoperative patients with meningioma. Patients diagnosed with meningioma after surgery in West China Hospital and Shangjin Hospital of Sichuan University from 2009 to 2016 were included in the study cohort. As the training cohort (n = 1975), independent risk factors associated with high-grade meningioma were used to establish the Nomogram model. which was validated in a subsequent cohort (n = 1048) from 2017 to 2019 in our hospital. Logistic regression (LR), XGboost, Adaboost, Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Random Forest (RF) models were determined using F1 score, recall, accuracy, the area under the curve (ROC), calibration plot and decision curve analysis (DCA) were used to evaluate the different models. Logistic regression showed better predictive performance and interpretability than machine learning. Gender, recurrence history, T1 signal intensity, enhanced signal degree, peritumoral edema, tumor diameter, cystic, location, and NLR index were identified as independent risk factors and added to the nomogram. The AUC (Area Under Curve) value of RF was 0.812 in the training set, 0.807 in the internal validation set, and 0.842 in the external validation set. The calibration curve and DCA (Decision Curve Analysis) indicated that it had better prediction efficiency of LR than others. The Nomogram preoperative prediction model of meningioma of WHO II and III grades showed effective prediction ability. While machine learning exhibits strong fitting ability, it performs poorly in the validation set.

Malignant transformation of meningioma: Case report.

Meningiomas are mostly benign brain tumors with minimal malignant cases. Anaplastic meningioma has malignant morphological characteristics and a World Health Organization grade of III. The present study reports a case of an occipital meningioma in a patient who initially chose observation and follow-up after diagnosis. The patient ultimately underwent surgery due to the enlargement of the tumor and the development of visual field defects after a decade of imaging follow-up. The postoperative pathology slides indicated the presence of an anaplastic meningioma (World Health Organization-grade III). The patient's diagnosis was established through cranial magnetic resonance imaging, which revealed an irregular mixed mass in the right occipital region with isointense T1 and hypointense T2 signal, irregular lobulation, and a maximum diameter of approximately 5.4 cm. Heterogenous enhancement was observed in the contrast-enhanced scan. The patient opted for surgical intervention to remove the tumor, and the pathology slides of the tumor sample confirmed the diagnosis of anaplastic meningioma. The patient also received radiotherapy (40Gy/15fr). No recurrence was observed during the 9-month follow-up. This case highlights the potential for low-grade meningiomas to undergo malignant transformation, particularly in the presence of irregular lobulation, peritumoral brain edema, and heterogeneous enhancement on contrast-enhanced scans. Total excision (Simpson grade I) is the preferred treatment option, and long-term imaging follow-up is recommended.

Prospects of pharmacological regulation of aquaporin function in CNS diseases

The review analyzes the results of scientific research on the role of aquaporins in the pathogenesis of CNS diseases and the possibility of their pharmacological regulation.
 Aquaporins (AQP) are proteins involved in the transmembrane transport of water and other substances. They form the water channels of cell membranes and are widely represented in various mammalian cells, including the membranes of human brain and spinal cord cells. To date, about 300 types of proteins of the aquaporin family have been discovered, of which 13 (AQP0AQP12) have been identified in human cells. Localization of different types of AQP in CNS structures, their functional activity and involvement in the development of CNS diseases differ. There are mainly three types of AQPs in the central nervous system: AQP1, AQP4 and AQP9. The results of scientific research indicate the most important role of AQP in maintaining water-salt homeostasis and ensuring physiological processes in the central nervous system, and also confirm the role of AQP in the pathogenesis of a number of diseases of the central nervous system (cerebral edema of various genesis, invasion of tumor cells and the formation of peritumorous edema, in the development of autoimmune diseases opticomyelitis, Alzheimers disease). Pharmacological regulation of the functional activity of aquaporins can influence the course of these diseases. Therefore, there is a natural interest in drugs that can change the expression of AQP.
 Proteins of the aquaporin family provide transmembrane transport of water and play an essential role in the development of pathological conditions of the central nervous system. They can be potential targets for pharmacological effects in a number of diseases of the central nervous system. The search and study of drugs affecting the expression and functional activity of AQP is pathogenetically justified and is a promising direction in the development of pharmacotherapy strategies for cerebral edema, malignant brain tumors and other CNS diseases.

Comparison of 20% mannitol and 3% hypertonic saline for intraoperative brain relaxation during supratentorial brain tumour craniotomy in patients with a midline shift

Purpose of the studyA prospective, randomized, double-blind study was designed to assess differences in brain relaxation between 20% mannitol and 3% hypertonic saline (HS) during elective supratentorial brain tumour surgery in patients with midline shift. Material and methodsSixty patients undergoing supratentorial craniotomy for tumour resection were enrolled to receive either 5mL/kg of 20% mannitol (n=30) or 3% HS (n=30) administered at skin incision. PCO2 in arterial blood was maintained within 35–40mmHg and arterial blood pressure was controlled within baseline values ±20%. The primary outcome was the proportion of satisfactory brain relaxation. The surgeon assessed brain relaxation on a four-point scale (1=excellent with no swelling, 2=minimal swelling, 3=serious swelling not requiring treatment, 4=severe swelling requiring treatment). Postsurgical intracranial changes determined by imaging techniques, postoperative complications, PACU and hospital stay, and mortality at 30 days were also recorded. Appropriate statistical tests were used for comparison; P<0.05 was considered as significant. This trial was registered in Eudract.ema.europa.eu (#2021-006290-40). ResultsThere was no difference in brain relaxation: 2.00 [1.00–2.00] and 2.00 [1.75–3.00] for patients in mannitol and HS groups, respectively (P=0.804). Tumour size (OR: 0.99, 95% CI: 0.99–1.01; P=0.371), peritumoral oedema classification (OR: 0.57, 95% CI: 0.11–2.84; P=0.493), mass effect (OR: 0.86, 95% CI: 0.16–4.87; P=0.864), anaesthesia (OR: 4.88, 95% CI: 0.82–28.96; P=0.081) and midline shift (OR: 5.00, 95% CI: 0.84–29.70; P=0.077) did not have a significant influence on brain swelling in patients treated with either mannitol or HS. No significant differences in perioperative outcomes, mortality and length of PACU and hospital stay were observed. Conclusions5mL/kg of 20% mannitol or 3% HS result in similar brain relaxation scores in patients undergoing craniotomy for supratentorial brain tumour with midline shift.

Intraoperative shear-wave elastography and superb microvascular imaging contribute to the glioma grading

BackgroundTo explore the diagnostic value and feasibility of shear wave elastography and superb microvascular imaging in the grading diagnosis of glioma intraoperatively. Materials and methodsForty-nine patients with glioma were included in this study. B-mode ultrasonography, Young's modulus in shear-wave elastography (SWE) and vascular architecture in superb microvascular imaging(SMI) of tumor tissue and peritumoral tissue were analyzed. Receiver operating characteristic(ROC) curve analysis was used to evaluate the diagnostic effect of SWE. Logistic regression model was used to calculate the prediction probability of HGG diagnosis. ResultsCompared with LGG, HGG was often characterized by peritumoral edema in B mode (P < 0.05). There was a significant difference in Young's modulus between HGG and LGG; the diagnostic threshold of HGG and LGG was 13.05 kPa, the sensitivity was 78.3%, and the specificity was 76.9%. The vascular architectures of the tumor tissue and peritumoral tissues of HGG and LGG were significantly different (P < 0.05). The vascular architectures of peritumoral tissue in HGG often characterized by distorted blood flow signals surrounding the tumor (14/26,53.8%); in the tumor tissue, HGG often presents as dilated and bent vessels(19/26,73.1%). The elasticity value of SWE and the tumor vascular architectures of SMI were correlated with the diagnosis of HGG. ConclusionIntraoperative ultrasound (ioUS), especially SWE, and SMI are beneficial for the differentiation of HGG and LGG and may help optimize clinical surgical procedures.

Imaging presentation of extraskeletal osteosarcomas on CT and MRI and correlation with patients outcome: A two-center retrospective study of 54 patients

PurposeThe purpose of this study was to analyze the imaging features of extraskeletal osteosarcomas (ESOS) on computed tomography (CT) and magnetic resonance imaging (MRI) and to investigate their associations with overall survival (OS) using uni- and multivariable survival analyses. Materials and methodsThis two-center retrospective study included all consecutive adult patients between 2008 and 2021 with histopathologically-proven ESOS who underwent pre-treatment CT and/or MRI. Clinical and histological characteristics, ESOS presentation on CT and MRI, treatment and outcomes were reported. Survival analyses were performed using Kaplan-Meier analysis and Cox regressions. Associations between imaging features and OS were searched using uni- and multivariable analyses. ResultsFifty-four patients were included (30/54 [56%] men, median age: 67.5 years). Twenty-four died of ESOS (median OS: 18 months). ESOS were mostly deep-seated (46/54, 85%) in the lower limb (27/54, 50%) with a median size of 95 mm (interquartile range: 64, 142; range: 21–289 mm). Mineralization was seen on 26/42 (62%) patients, mainly gross-amorphous (18/26; 69%). ESOS were generally highly heterogeneous on T2-weighted images (38/48; 79%) and contrast-enhanced (CE) T1-weighted images (29/40; 72%), with necrosis (39/40; 97%), well-defined or focally infiltrative margins (39/47; 83%), with moderate peritumoral edema (39/47; 83%) and rim-like peripheral enhancement (17/40; 42%). Size, location, mineralization on CT, signal intensity heterogeneity on T1-, T2- and CE-T1-weighted images and hemorragic signal on MRI were associated with poorer OS (range of log-rank P = 0.0069–0.0485). At multivariable analysis, hemorragic signal and signal intensity heterogeneity on T2-weighted images remained predictive for poorer OS (hazard ratio [HR] = 2.68, P = 0.0299; HR = 9.85, P = 0.0262, respectively) ConclusionESOS typically presents as mineralized heterogeneous and necrotic soft tissue tumor with a possible rim-like enhancement and limited peritumoral abnormalities. MRI may help estimate outcome of patients with ESOS.

Clinical, Morphological, and Molecular Study on Grade 2 and 3 Pleomorphic Xanthoastrocytoma.

Pleomorphic xanthoastrocytoma (PXA) is an uncommon astrocytoma that tends to occur in children and young adults and has a relatively favorable prognosis. The 2021 WHO classification of tumors of the central nervous system (CNS WHO), 5th edition, rates PXAs as grade 2 and grade 3. The histological grading was based on mitotic activity (≥2.5 mitoses/mm2). This study specifically evaluates the clinical, morphological, and, especially, the molecular characteristics of grade 2 and 3 PXAs. Between 2003 and 2021, we characterized 53 tumors with histologically defined grade 2 PXA (n = 36, 68%) and grade 3 PXA (n = 17, 32%). Compared with grade 2 PXA, grade 3 PXA has a deeper location and no superiority in the temporal lobe and is more likely to be accompanied by peritumoral edema. In histomorphology, epithelioid cells and necrosis were more likely to occur in grade 3 PXA. Molecular analysis found that the TERT promoter mutation was more prevalent in grade 3 PXA than in grade 2 PXA (35% vs. 3%; p = 0.0005) and all mutation sites were C228T. The cases without BRAF V600E mutation or with necrosis in grade 3 PXA had a poor prognosis (p = 0.01). These data define PXA as a heterogeneous astrocytoma. Grade 2 and grade 3 PXAs have different clinical and histological characteristics as well as distinct molecular profiles. TERT promoter mutations may be a significant genetic event associated with anaplastic progression. Necrosis and BRAF V600E mutation play an important role in the prognosis of grade 3 PXA.

An initial study on the predictive value using multiple MRI characteristics for Ki-67 labeling index in glioma

Background and purposeKi-67 labeling index (LI) is an important indicator of tumor cell proliferation in glioma, which can only be obtained by postoperative biopsy at present. This study aimed to explore the correlation between Ki-67 LI and apparent diffusion coefficient (ADC) parameters and to predict the level of Ki-67 LI noninvasively before surgery by multiple MRI characteristics.MethodsPreoperative MRI data of 166 patients with pathologically confirmed glioma in our hospital from 2016 to 2020 were retrospectively analyzed. The cut-off point of Ki-67 LI for glioma grading was defined. The differences in MRI characteristics were compared between the low and high Ki-67 LI groups. The receiver operating characteristic (ROC) curve was used to estimate the accuracy of each ADC parameter in predicting the Ki-67 level, and finally a multivariate logistic regression model was constructed based on the results of ROC analysis.ResultsADCmin, ADCmean, rADCmin, rADCmean and Ki-67 LI showed a negative correlation (r = − 0.478, r = − 0.369, r = − 0.488, r = − 0.388, all P < 0.001). The Ki-67 LI of low-grade gliomas (LGGs) was different from that of high-grade gliomas (HGGs), and the cut-off point of Ki-67 LI for distinguishing LGGs from HGGs was 9.5%, with an area under the ROC curve (AUROC) of 0.962 (95%CI 0.933–0.990). The ADC parameters in the high Ki-67 group were significantly lower than those in the low Ki-67 group (all P < 0.05). The peritumoral edema (PTE) of gliomas in the high Ki-67 LI group was higher than that in the low Ki-67 LI group (P < 0.05). The AUROC of Ki-67 LI level assessed by the multivariate logistic regression model was 0.800 (95%CI 0.721–0.879).ConclusionsThere was a negative correlation between ADC parameters and Ki-67 LI, and the multivariate logistic regression model combined with peritumoral edema and ADC parameters could improve the prediction ability of Ki-67 LI.

Importance of Age and Noncontrast-Enhancing Tumor as Biomarkers for Isocitrate Dehydrogenase-Mutant Glioblastoma: A Multicenter Study.

This study aimed to investigate the most useful clinical and magnetic resonance imaging (MRI) parameters for differentiating isocitrate dehydrogenase (IDH)-mutant and -wildtype glioblastomas in the 2016 World Health Organization Classification of Tumors of the Central Nervous System. This multicenter study included 327 patients with IDH-mutant or IDH-wildtype glioblastoma in the 2016 World Health Organization classification who preoperatively underwent MRI. Isocitrate dehydrogenase mutation status was determined by immunohistochemistry, high-resolution melting analysis, and/or IDH1/2 sequencing. Three radiologists independently reviewed the tumor location, tumor contrast enhancement, noncontrast-enhancing tumor (nCET), and peritumoral edema. Two radiologists independently measured the maximum tumor size and mean and minimum apparent diffusion coefficients of the tumor. Univariate and multivariate logistic regression analyses with an odds ratio (OR) were performed. The tumors were IDH-wildtype glioblastoma in 306 cases and IDH-mutant glioblastoma in 21. Interobserver agreement for both qualitative and quantitative evaluations was moderate to excellent. The univariate analyses revealed a significant difference in age, seizure, tumor contrast enhancement, and nCET (P < 0.05). The multivariate analysis revealed significant difference in age for all 3 readers (reader 1, odds ratio [OR] = 0.960, P = 0.012; reader 2, OR = 0.966, P = 0.048; reader 3, OR = 0.964, P = 0.026) and nCET for 2 readers (reader 1, OR = 3.082, P = 0.080; reader 2, OR = 4.500, P = 0.003; reader 3, OR = 3.078, P = 0.022). Age and nCET are the most useful parameters among the clinical and MRI parameters for differentiating IDH-mutant and IDH-wildtype glioblastomas.

Usefulness of a Rim-Enhancing Pattern on the Contrast-Enhanced 3D-FLAIR Sequence and MRI Characteristics for Distinguishing Meningioma and Malignant Dural-Based Tumor.

Meningiomas are the most common type of extra-axial dural-based tumors; however, malignant dural-based tumors can mimic meningiomas on imaging. The aim of this study was to determine the efficacy of differentiating meningiomas from malignant dural-based tumors by using rim-enhancement patterns on a contrast-enhanced FLAIR sequence and MR imaging characteristics. This retrospective study included 102 patients with meningiomas and 31 patients with malignant dural-based tumors who underwent pretreatment MR imaging. The rim-enhancement patterns on contrast-enhanced FLAIR and MR imaging characteristics, including the dural tail sign, hyperostosis, bony destruction, leptomeningeal enhancement, peritumoral edema, T2-weighted signal intensity, and tumor enhancement were evaluated. Complete rim enhancement of the tumor-brain interface on contrast-enhanced FLAIR (contrast-enhanced-FLAIR rim sign) was present in most meningiomas (91/102, 89.2%) and at significantly greater frequency than in malignant dural-based tumors (2/31, 6.5%) (P < .001). Complete contrast-enhanced FLAIR rim enhancement provided high sensitivity (89.2%), specificity (93.5%), and accuracy (90.2%) for diagnosing meningioma. Additionally, hyperostosis was an MR imaging characteristic that suggested a diagnosis of meningioma. In contrast, bony destruction with cortical breakthrough and leptomeningeal enhancement suggested malignant dural-based tumors. There were limitations of meningiomas of <2.0 cm or at cavernous sinus locations that did not demonstrate contrast-enhanced FLAIR rim enhancement. The rim-enhancement pattern on contrast-enhanced FLAIR could help differentiate meningiomas and malignant dural-based tumors. The presence of complete rim enhancement on contrast-enhanced FLAIR was a robust predictive sign for meningioma.

Deep learning automates bidimensional and volumetric tumor burden measurement from MRI in pre- and post-operative glioblastoma patients

Tumor burden assessment by magnetic resonance imaging (MRI) is central to the evaluation of treatment response for glioblastoma. This assessment is, however, complex to perform and associated with high variability due to the high heterogeneity and complexity of the disease. In this work, we tackle this issue and propose a deep learning pipeline for the fully automated end-to-end analysis of glioblastoma patients. Our approach simultaneously identifies tumor sub-regions, including the enhancing tumor, peritumoral edema and surgical cavity in the first step, and then calculates the volumetric and bidimensional measurements that follow the current Response Assessment in Neuro-Oncology (RANO) criteria. Also, we introduce a rigorous manual annotation process which was followed to delineate the tumor sub-regions by the human experts, and to capture their segmentation confidences that are later used while training deep learning models. The results of our extensive experimental study performed over 760 pre-operative and 504 post-operative adult patients with glioma obtained from the public database (acquired at 19 sites in years 2021–2020) and from a clinical treatment trial (47 and 69 sites for pre-/post-operative patients, 2009–2011) and backed up with thorough quantitative, qualitative and statistical analysis revealed that our pipeline performs accurate segmentation of pre- and post-operative MRIs in a fraction of the manual delineation time (up to 20 times faster than humans). Volumetric measurements were in strong agreement with experts with the Intraclass Correlation Coefficient (ICC): 0.959, 0.703, 0.960 for ET, ED, and cavity. Similarly, automated RANO compared favorably with experienced readers (ICC: 0.681 and 0.866) producing consistent and accurate results. Additionally, we showed that RANO measurements are not always sufficient to quantify tumor burden. The high performance of the automated tumor burden measurement highlights the potential of the tool for considerably improving and simplifying radiological evaluation of glioblastoma in clinical trials and clinical practice.

Does the apparent diffusion coefficient from diffusion-weighted MRI imaging aid in the characterization of malignant soft tissue tumors and sarcomas.

To identify trends in apparent diffusion coefficient (ADC) measurements from diffusion-weighted imaging (DWI) with respect to tumor type classification and other tumor characteristics whether common malignant soft tissue tumors can be distinguished. A consecutive series of extremity malignant soft tissue tumors and soft tissue sarcomas (STS) among 78 adult patients with conventional MRI and DWI were included. Each case was evaluated with respect to T1/T2 signal alterations and heterogeneity, presence of peritumoral edema, necrosis, cystic changes, internal hemorrhage, and maximum longitudinal dimension blinded to the histology. The ADC mean and minimum were obtained using a free-hand region of interest of the whole tumor and the darkest (lowest signal area) ADC area of the tumor. Kruskal-Wallis and Wilcoxon Rank-Sum Tests were used to determine associations and significance between tumor subtypes. Intraclass correlation (ICC) and kappa calculations were utilized to assess inter-reader agreements for ADC values and reader diagnosis. Liposarcomas showed more heterogenous T1W images with hyperintense T1W signal when compared to tumors not classified as liposarcoma (P = 0.046 and P = 0.010, respectively). Liposarcomas were relatively consistent in demonstrating an absence of hemorrhage (81.8%) while undifferentiated pleomorphic sarcomas consistently showed intralesional hemorrhage (90%). When comparing individual tumor classifications against the rest of the samples, lymphomas registered lower mean and minimum ADC values in the whole tumor and in themost hypointense area of the tumor for both readers (P < 0.05). The interobserver agreement between the two readers was good to excellent for all four ADC measurements (ICC = 0.65-0.98). Diffusion-weighted imaging generated ADC measurements are reproducible but currently offer limited insight in being able to differentiate among different malignant soft tissue tumor and sarcoma histologies.T1W and T2W signal characteristics also offer limited insight indifferentiating between soft tissue malignancies.

Peritumoural Oedema as a Predictor of Overall Survival for Patients with Posterior Fossa Metastases.

To analyse the relationship between peritumoural oedema volume and tumour volume in relation to the impact of metastatic posterior fossa tumour survival rates. An observational study. Umraniye Training and Research Hospital, İstanbul, Turkey, from 2011-2021. Fifty-six cancer patients who had been operated upon for cerebellar metastases were analysed retrospectively. To investigate the effect of oedema on survival, patients with a single cerebellar metastasis were evaluated retrospectively. Those patients had a single metastasis located in the cerebellum and did not receive radiotherapy or corticosteroids before surgery. OsiriX MD DICOM viewer was used to calculate the volumes of the tumour and the oedema using fluid-attenuated inversion recovery (FLAIR) and contrast-enhanced magnetic resonance imaging (MRI). The patients were separated into two groups, and the cut-off limit for the oedema to-tumour ratio was set to two. Survival analysis was performed on the two groups. When the primary sites of the tumours were evaluated, 60.7% were located in the lungs (n = 34), 10.7% were located in the breasts (n = 6), 10.7% were located in the gastrointestinal tract (n = 6), 7.1% were located in the renal region (n = 4), 5.4% were located in the gynaecologic tract (n = 3), and 5.4% were located in other parts of the body (n = 3). A univariate analysis showed that overall survival duration was significantly longer in the subgroup with breast cancer (83.3%) and in those patients with a peritumoural oedema volume to tumour volume ratio of less than two (27.6%, p <0.05). Negative prognostic factors were lung cancer and high peritumoural oedema volume. Significant peritumoural oedema was linked to a poor prognosis for cancer patients with a single cerebellar metastasis, especially with lung cancer as the primary source. Cerebellar metastases, Cerebellum, OsiriX MD, Tumour volume.

Impact of peritumoral brain edema on pre- and postoperative clinical conditions and on long-term outcomes in patients with intracranial meningiomas

BackgroundPeritumoral brain edema (PTBE) is a common complication related to intracranial meningiomas. In several studies, researchers have investigated the pathogenesis of PTBE, and the factors involved in its development in patients with intracranial meningiomas have been reported. However, very little is known about the clinical effect of PTBE on patients with intracranial meningiomas; therefore, a systematic examination of this matter is necessary.MethodsIn this study, we performed a systematic examination of 696 patients with primary intracranial meningiomas to assess the effect of preoperative PTBE on preoperative symptoms, neurological deficits and postoperative complications, and long-term outcomes with a follow-up period of 16.8 years. We performed a univariate analysis and multiple regression for specific outcomes and adjusted for other relevant clinical factors.ResultsA total of 627 (90.1%) patients were symptomatic preoperatively. One hundred eighty-eight (90.8%) patients with small to moderate PTBE and 125 (98.4%) patients with severe PTBE presented with symptoms significantly more often than the 314 (86.7%) patients without PTBE (p < 0.001, univariate analysis). Cognitive deficits, palsy and seizure were significantly more present, preoperatively, in patients with PTBE than in patients without PTBE (p < 0.001, univariate analysis). Two hundred fifty-five (36.6%) patients experienced surgical and systemic complications postoperatively. The complication rate was significantly higher in patients with PTBE; 41.5% for patients with small to moderate PTBE and 52.8% for patients with severe PTBE, compared to 28.2% of patients without PTBE (p < 0.001, univariate analysis). Furthermore, pre- and postoperative KPS scores were significantly lower in patients with PTBE (p < 0.001). Patients with PTBE required additional medical support significantly more often (p < 0.001) and had a significantly longer hospital stay (p < 0.001). The mortality rate was higher in patients with PTBE immediately after surgery and in the follow-up period; however, the difference was not significant. The neurological condition of all patients improved in the follow-up and did not show significant differences between patients with and without preoperative PTBE (p = 0.6361). Multiple logistic regression analyses revealed a significant association between PTBE and the presence of preoperative cognitive deficits, the incidences of seizure and postoperative complications, and low pre- and postoperative KPS scores.ConclusionsPreoperative PTBE significantly increased the incidences of specific preoperative symptoms, neurological deficits and postoperative complications in patients with intracranial meningiomas. After surgery, patients with preoperative PTBE required medical support significantly more often than patients without PTBE. However, all patients had favorable outcomes after surgery.

The efficacy of preoperative MRI features in the diagnosis of meningioma WHO grade and brain invasion.

The preoperative MRI scans of meningiomas were analyzed based on the 2021 World Health Organization (WHO) Central Nervous System (CNS) Guidelines, and the efficacy of MRI features in diagnosing WHO grades and brain invasion was analyzed. The data of 675 patients with meningioma who underwent MRI in our hospital from 2006 to 2022, including 108 with brain invasion, were retrospectively analyzed. Referring to the WHO Guidelines for the Classification of Central Nervous System Tumors (Fifth Edition 2021), 17 features were analyzed, with age, sex and meningioma MRI features as risk factors for evaluating WHO grade and brain invasion. The risk factors were identified through multivariable logistic regression analysis, and their receiver operating characteristic (ROC) curves for predicting WHO grades and brain invasion were generated, and the area under the curve (AUC), sensitivity and specificity were calculated. Univariate analysis showed that sex, tumor size, lobulated sign, peritumoral edema, vascular flow void, bone invasion, tumor-brain interface, finger-like protrusion and mushroom sign were significant for diagnosing meningioma WHO grades, while these features and ADC value were significant for predicting brain invasion (P < 0.05). Multivariable logistic regression analysis showed that the lobulated sign, tumor-brain interface, finger-like protrusion, mushroom sign and bone invasion were independent risk factors for diagnosing meningioma WHO grades, while the above features, tumor size and ADC value were independent risk factors for diagnosing brain invasion (P < 0.05). The tumor-brain interface had the highest efficacy in evaluating WHO grade and brain invasion, with AUCs of 0.779 and 0.860, respectively. Combined, the variables had AUCs of 0.834 and 0.935 for determining WHO grade and brain invasion, respectively. Preoperative MRI has excellent performance in diagnosing meningioma WHO grade and brain invasion, while the tumor-brain interface serves as a key factor. The preoperative MRI characteristics of meningioma can help predict WHO grade and brain invasion, thus facilitating complete lesion resection and improving patient prognosis.

Imaging findings of supratentorial embryonal tumor with multilayered rosettes in children

We analyzed and summarized the imaging characteristics and clinical data of seven pediatric supratentorial embryonal tumors with multilayered rosettes (ETMR). There were four boys and three girls aged from two to six years old. Pediatric supratentorial ETMR often presented large cystic and solid mass, calcification, significant mass effect and mild peritumoral edema. The solid part often showed heterogeneous mild enhancement. In combination with the location of tumor and age of onset, the typical imaging manifestations of supratentorial ETMR in children are valuable for accurate diagnosis.

Analysis of the common complications and recurrence-related factors of superior parasagittal sinus meningioma.

Parasagittal meningioma resection is prone to postoperative complications and tumor recurrence because the tumor invades the superior sagittal sinus. This study aimed to clarify the incidence of perioperative complications and the recurrence of superior sagittal paranasal meningiomas and explored potential predictors in this context. The study retrospectively reviewed the clinical, imaging, and follow-up data of parasagittal meningiomas among patients who underwent microsurgical resection in the authors' institution from January 2008 to December 2017. Univariate and multivariate logistic regression analyses were conducted to explore independent predictors of perioperative complications and tumor recurrence. A total of 212 parasagittal meningioma patients were included in this study. The incidence of perioperative complications was 23.6% (50/212), and perioperative death occurred in 6 (2.8%) patients. In univariate and multivariate logistic regression analyses of perioperative complications, peritumoral edema ≥1 cm (odds ratio [OR] 2.163, 95% confidence interval [CI] 1.057-4.428, P = 0.035) and the Sindou invasion Class V-VI(OR0.018, 95% CI 1.248-11.064, P = 0.018) were independent predictors. After an average of 83 (39-154) months of clinical follow up among the living 206 patients, 22 (10.7%) patients showed tumor recurrence. In univariate and multivariate logistic regression analyses of tumor recurrence, the Sindou invasion Class III-IV (OR 5.539, 95%CI 1.469-20.884, P = 0.011) and the Sindou invasion Class V-VI (OR 9.144, 95%CI 2.215-37.757, P = 0.002) were independent predictors. Peritumoral edema ≥1 cm and the Sindou invasion Class V-VI were the independent predictors of perioperative complications, and the Sindou invasion Class III-IV and the Sindou invasion Class V-VI were the independent predictors of tumor recurrence. The part of the parasagittal meningioma involving the sinus wall should be actively removed to the largest degree possible to reduce the recurrence rate.

MRI radiomic features of peritumoral edema may predict the recurrence sites of glioblastoma multiforme.

As one of the most aggressive malignant tumor in the central nervous system, the main cause of poor outcome of glioblastoma (GBM) is recurrence, a non-invasive method which can predict the area of recurrence pre-operation is necessary.To investigate whether there is radiological heterogeneity within peritumoral edema and identify the reproducible radiomic features predictive of the sites of recurrence of glioblastoma(GBM), which may be of value to optimize patients' management. The clinical information and MR images (contrast-enhanced T1 weighted and FLAIR sequences) of 22 patients who have been histologically proven glioblastoma, were retrospectively evaluated. Kaplan-Meier methods was used for survival analysis. Oedematous regions were manually segmented by an expert into recurrence region, non-recurrence region. A set of 94 radiomic features were obtained from each region using the function of analyzing MR image of 3D slicer. Paired t test was performed to identify the features existing significant difference. Subsequently, the data of two patients from TCGA database was used to evaluate whether these features have clinical value. Ten features with significant differences between the recurrence and non-recurrence subregions were identified and verified on two individual patients from the TCGA database with pathologically confirmed diagnosis of GBM. Our results suggested that heterogeneity does exist in peritumoral edema, indicating that the radiomic features of peritumoral edema from routine MR images can be utilized to predict the sites of GBM recurrence. Our findings may further guide the surgical treatment strategy for GBM.