Peritumoral Edema Research Articles

Training and Comparison of nnU-Net and DeepMedic Methods for Autosegmentation of Pediatric Brain Tumors.

Tumor segmentation is essential in surgical and treatment planning and response assessment and monitoring in pediatric brain tumors, the leading cause of cancer-related death among children. However, manual segmentation is time-consuming and has high interoperator variability, underscoring the need for more efficient methods. After training, we compared 2 deep-learning-based 3D segmentation models, DeepMedic and nnU-Net, with pediatric-specific multi-institutional brain tumor data based on multiparametric MR images. Multiparametric preoperative MR imaging scans of 339 pediatric patients (n = 293 internal and n = 46 external cohorts) with a variety of tumor subtypes were preprocessed and manually segmented into 4 tumor subregions, ie, enhancing tumor, nonenhancing tumor, cystic components, and peritumoral edema. After training, performances of the 2 models on internal and external test sets were evaluated with reference to ground truth manual segmentations. Additionally, concordance was assessed by comparing the volume of the subregions as a percentage of the whole tumor between model predictions and ground truth segmentations using the Pearson or Spearman correlation coefficients and the Bland-Altman method. The mean Dice score for nnU-Net internal test set was 0.9 (SD, 0.07) (median, 0.94) for whole tumor; 0.77 (SD, 0.29) for enhancing tumor; 0.66 (SD, 0.32) for nonenhancing tumor; 0.71 (SD, 0.33) for cystic components, and 0.71 (SD, 0.40) for peritumoral edema, respectively. For DeepMedic, the mean Dice scores were 0.82 (SD, 0.16) for whole tumor; 0.66 (SD, 0.32) for enhancing tumor; 0.48 (SD, 0.27) for nonenhancing tumor; 0.48 (SD, 0.36) for cystic components, and 0.19 (SD, 0.33) for peritumoral edema, respectively. Dice scores were significantly higher for nnU-Net (P ≤ .01). Correlation coefficients for tumor subregion percentage volumes were higher (0.98 versus 0.91 for enhancing tumor, 0.97 versus 0.75 for nonenhancing tumor, 0.98 versus 0.80 for cystic components, 0.95 versus 0.33 for peritumoral edema in the internal test set). Bland-Altman plots were better for nnU-Net compared with DeepMedic. External validation of the trained nnU-Net model on the multi-institutional Brain Tumor Segmentation Challenge in Pediatrics (BraTS-PEDs) 2023 data set revealed high generalization capability in the segmentation of whole tumor, tumor core (a combination of enhancing tumor, nonenhancing tumor, and cystic components), and enhancing tumor with mean Dice scores of 0.87 (SD, 0.13) (median, 0.91), 0.83 (SD, 0.18) (median, 0.89), and 0.48 (SD, 0.38) (median, 0.58), respectively. The pediatric-specific data-trained nnU-Net model is superior to DeepMedic for whole tumor and subregion segmentation of pediatric brain tumors.

The Observation at Mean Oedema Index Variations with Location and Histological subtypes in Supratentorial WHO G-I Meningiomas

Background: The term meningioma is the noncommittal, all-encompassing name coined by Harvey Cushing for this tumor of meninges which is usually benign. The severity and variety of the peritumoral brain oedema may limit operative exposure and increase the difficulties of intraoperative procedures; however, its pathogenesis is not clearly documented. Several factors, such as tumor size, location and histology, mechanical compression of draining vein by the tumor have been proposed as mechanism of peritumoral brain oedema Aims: The objective of this study was to determination of mean oedema index in different locations and histological subtypes in patients with supratentorial WHO GI meningiomas Methods: The study was conducted in the Department of Neurosurgery, Bangabandhu Sheikh Mujib Medical University, Dhaka, Bangladesh from September, 2016 to March, 2018. This study was a cross sectional study. Data collection sheets were used to collect necessary information. Total 75 cases were selected consistent with inclusion and exclusion criteria. Tumor volume and localization and the presence of peritumoral brain oedema (PTBOe) were determined by MRI (Magnetic Resonance Image). All patients underwent microsurgical removal of tumor. Surgically resected meningiomas were classified histopathologically based on criteria of the new World Health Organization (WHO) classification. Regarding location and histological subtypes of tumor the study population were divided into 6 groups and 8 groups respectively.Statistical analyses were done by Statistical Packages for Social Sciences (SPSS-v.25). Results: A total 75 cases were selected consistent with inclusion and exclusion criteria from September, 2016 to March, 2018. Regarding location; the mean oedema index for each of the six groups was calculated and recorded. The F value was 5.97 and the P-value was 0.0001 which was less than 0.05. This result signifies that there was association between perilesional oedema in supratentorial meningioma to its location. So, Mean Oedema Index in Intracranial Supratentorial Meningiomas vary with its location. On the other hand, regarding histopathological subtypes, meningiomaswere divided into eight groups-the mean oedema index of each of the eight groups was calculated and recorded. The F value was 1.62 and P-value was 0.145 which was more than 0.05. This result signifies that there was no association between perilesional oedema in supratentorial meningioma to its histological subtypes. So mean oedema index in intracranial supratentorial meningiomas does not vary with its histological subtypes. Conclusion: Mean Oedema Index in Intracranial Supratentorial Meningiomas vary with its location but does not vary with histological subtypes Bang. J Neurosurgery 2023; 13(1): 10-13

Abstract PO3-07-12: Effect of neoadjuvant chemotherapy on peritumoral edema in early stage breast cancer and its prognostic value

Abstract Objectives: We aimed to evaluate the effect of neoadjuvant chemotherapy (NAC) on peritumoral edema (PE) and its prognostic value in operable breast cancer. Materials & Methods: This retrospective study included 128 cT1-4N0-3M0 breast cancer patients who underwent contrast-enhanced magnetic resonance imaging (MRI) of the breast before and after anthracycline- and/or taxane-based NAC, followed by curative surgery at our hospital, between 2006 and 2016. T2-weighted MRI revealed PE, and PE before NAC (pre-PE) and PE after NAC (residual PE) were evaluated. The correlation between the presence or absence of PE and relapse-free survival was evaluated using a log-rank test and multivariable Cox regression analysis. The risk of recurrence was stratified according to the residual cancer burden (RCB). Results: Pre-PE was observed in 64 out of 128 patients (50%). Among 64 patients with pre-PE-positive breast cancer, residual PE was observed in 21 (32.8%). In the log-rank test, breast cancer with residual PE had a poorer prognosis than breast cancer with PE that had disappeared (p < 0.0001). In the multivariable Cox regression analysis, residual PE was a significant factor of poor prognosis (RR, 20.5; 95% confidence interval, 5.3–108.2; p < 0.0001). Regarding RCB stratification, compared to patients with breast cancer with disappeared PE, those with breast cancer with residual PE exhibited significantly poor prognosis in class II and class III (p = 0.006, 0.02). Conclusion: In breast cancer with PE, residual PE after NAC is a significant factor related to poor prognosis. Effect of neoadjuvant chemotherapy on peritumoral edema in patients with breast cancer and its clinical significance XX XX Citation Format: Hideo Shigematsu, Mutsumi Fujimoto, Yoshie Kobayashi, Tomoyuki Yoshiyama, Noriaki Matsuura, Daisuke Komoto, Kazuya Kuraoka. Effect of neoadjuvant chemotherapy on peritumoral edema in early stage breast cancer and its prognostic value [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-07-12.

Advanced diffusion MRI provides evidence for altered axonal microstructure and gradual peritumoral infiltration in GBM in comparison to brain metastases

PurposeIn contrast to peritumoral edema in metastases, GBM is histopathologically characterized by infiltrating tumor cells within the T2 signal alterations. We hypothesized that depending on the distance from the outline of the contrast-enhancing tumor we might reveal imaging evidence of gradual peritumoral infiltration in GBM and predominantly vasogenic edema around metastases. We thus investigated the gradual change of advanced diffusion metrics with the peritumoral zone in metastases and GBM.MethodsIn 30 patients with GBM and 28 with brain metastases, peritumoral T2 hyperintensity was segmented in 33% partitions based on the total volume beginning at the enhancing tumor margin and divided into inner, middle and outer zones. Diffusion Tensor Imaging (DTI)-derived fractional anisotropy and mean diffusivity as well as Diffusion Microstructure Imaging (DMI)-based parameters Dax-intra, Dax-extra, V‑CSF and V-intra were employed to assess group-wise differences between inner and outer zones as well as within-group gradients between the inner and outer zones.ResultsIn metastases, fractional anisotropy and Dax-extra were significantly reduced in the inner zone compared to the outer zone (FA p = 0.01; Dax-extra p = 0.03). In GBM, we noted a reduced Dax-extra and significantly lower intraaxonal volume fraction (Dax-extra p = 0.008, V‑intra p = 0.006) accompanied by elevated axial intraaxonal diffusivity in the inner zone (p = 0.035). Between-group comparison of the outer to the inner zones revealed significantly higher gradients in metastases over GBM for FA (p = 0.04) as well as the axial diffusivity in the intra- (p = 0.02) and extraaxonal compartment (p < 0.001).ConclusionOur findings provide evidence of gradual alterations within the peritumoral zone of brain tumors. These are compatible with predominant (vasogenic) edema formation in metastases, whereas our findings in GBM are in line with an axonal destructive component in the immediate peritumoral area and evidence of tumor cell infiltration with accentuation in the tumor’s vicinity.

Predictors of salvage therapy for parasagittal meningiomas treated with primary surgery, radiosurgery, or surgery plus adjuvant radiotherapy

ObjectiveParasagittal meningiomas (PM) are treated with primary microsurgery, radiosurgery (SRS), or surgery with adjuvant radiation. We investigated predictors of tumor progression requiring salvage surgery or radiation treatment. We sought to determine whether primary treatment modality, or radiologic, histologic, and clinical variables were associated with tumor progression requiring salvage treatment. MethodsRetrospective study of 109 consecutive patients with PMs treated with primary surgery, radiation (RT), or surgery plus adjuvant RT (2000–2017) and minimum 5 years follow-up. Patient, radiologic, histologic, and treatment data were analyzed using standard statistical methods. ResultsMedian follow up was 8.5 years. Primary treatment for PM was surgery in 76 patients, radiation in 16 patients, and surgery plus adjuvant radiation in 17 patients. Forty percent of parasagittal meningiomas in our cohort required some form of salvage treatment. On univariate analysis, brain invasion (OR: 6.93, p < 0.01), WHO grade 2/3 (OR: 4.54, p < 0.01), peritumoral edema (OR: 2.81, p = 0.01), sagittal sinus invasion (OR: 6.36, p < 0.01), sagittal sinus occlusion (OR: 4.86, p < 0.01), and non-spherical shape (OR: 3.89, p < 0.01) were significantly associated with receiving salvage treatment. On multivariate analysis, superior sagittal sinus invasion (OR: 8.22, p = 0.01) and WHO grade 2&3 (OR: 7.58, p < 0.01) were independently associated with receiving salvage treatment. There was no difference in time to salvage therapy (p = 0.11) or time to progression (p = 0.43) between patients receiving primary surgery alone, RT alone, or surgery plus adjuvant RT. Patients who had initial surgery were more likely to have peritumoral edema on preoperative imaging (p = 0.01). Median tumor volume was 19.0 cm3 in patients receiving primary surgery, 5.3 cm3 for RT, and 24.4 cm3 for surgery plus adjuvant RT (p < 0.01). ConclusionSuperior sagittal sinus invasion and WHO grade 2/3 are independently associated with PM progression requiring salvage therapy regardless of extent of resection or primary treatment modality. Parasagittal meningiomas have a high rate of recurrence with 80.0% of patients with WHO grade 2/3 tumors with sinus invasion requiring salvage treatment whereas only 13.6% of the WHO grade 1 tumors without sinus invasion required salvage treatment. This information is useful when counseling patients about disease management and setting expectations.

Multiparametric MRI-based radiomic nomogram for predicting HER-2 2+ status of breast cancer

ObjectiveTo explore the application of multiparametric MRI-based radiomic nomogram for assessing HER-2 2+ status of breast cancer (BC) MethodsPatients with pathology-proven HER-2 2+ invasive BC, who underwent preoperative MRI were divided into training (72 patients, 21 HER-2-positive and 51 HER-2-negative) and validation (32 patients, 9 HER-2-positive and 23 HER-2-negative) sets by randomization. All were classified as HER-2 2+ FISH-positive (HER-2-positive) or -negative (HER-2-negative) according to IHC and FISH. The 3D VOI was drawn on MR images by two radiologists. ADC, T2WI, and DCE images were analyzed separately to extract features (n = 1906). L1 regularization, F-test, and other methods were used to reduce dimensionality. Binary radiomics prediction models using features from single or combined imaging sequences were constructed using logistic regression (LR) classifier then and validated on a validation dataset. To build a radiomics nomogram, multivariate LR analysis was conducted to identify independent indicators. An evaluation of the model's predictive efficacy was made using AUC. ResultsOn the basis of combined ADC, T2WI, and DCE images, ten radiomic features were extracted following feature dimensionality reduction. There was superior diagnostic efficiency of radiomic signature using all three sequences compared to either one or two sequences (AUC for training group: 0.883; AUC for validation group: 0.816). Based on multivariate LR analysis, radiomic signature and peritumoral edema were independent predictors for identifying HER-2 2 +. In both training and validation datasets, nomograms combining peritumoral edema and radiomics signature demonstrated an effective discrimination (AUCs were respectively 0.966 and 0. 884). ConclusionThe nomogram that incorporated peritumoral edema and multiparametric MRI-based radiomic signature can be used to effectively predict the HER-2 2+ status of BC.

Deep learning and radiomics-based approach to meningioma grading: exploring the potential value of peritumoral edema regions

Objective. To address the challenge of meningioma grading, this study aims to investigate the potential value of peritumoral edema (PTE) regions and proposes a unique approach that integrates radiomics and deep learning techniques. Approach. The primary focus is on developing a transfer learning-based meningioma feature extraction model (MFEM) that leverages both vision transformer (ViT) and convolutional neural network (CNN) architectures. Additionally, the study explores the significance of the PTE region in enhancing the grading process. Main results. The proposed method demonstrates excellent grading accuracy and robustness on a dataset of 98 meningioma patients. It achieves an accuracy of 92.86%, precision of 93.44%, sensitivity of 95%, and specificity of 89.47%. Significance. This study provides valuable insights into preoperative meningioma grading by introducing an innovative method that combines radiomics and deep learning techniques. The approach not only enhances accuracy but also reduces observer subjectivity, thereby contributing to improved clinical decision-making processes.

Time course of tumorigenesis of a newly developed sporadic hemangioblastoma in an elderly patient: illustrative case.

von Hippel-Lindau disease-associated hemangioblastomas (HBs) account for 20%-30% of all HB cases, with the appearance of new lesions often observed in the natural course of the disease. By comparison, the development of new lesions is rare in patients with sporadic HB. A 65-year-old man underwent clipping for an unruptured aneurysm of the anterior communicating artery. Fourteen years later, follow-up magnetic resonance imaging (MRI) revealed a strongly enhanced mass in the right cerebellar hemisphere, diagnosed as a sporadic HB. A retrospective review of MRI studies obtained over the follow-up period revealed the gradual development of peritumoral edema and vascularization before mass formation. Newly appearing high-intensity T2 lesions in the cerebellum may represent a preliminary stage of tumorigenesis. Careful monitoring of these patients would be indicated, which could provide options for early treatment to improve patient outcomes.

Perifocal edema is a risk factor for preoperative seizures in patients with meningioma WHO grade 2 and 3

BackgroundPatients with intracranial meningiomas frequently suffer from tumor-related seizures prior to resection, impacting patients’ quality of life. We aimed to elaborate on incidence and predictors for seizures in a patient cohort with meningiomas WHO grade 2 and 3.MethodsWe retrospectively searched for patients with meningioma WHO grade 2 and 3 according to the 2021 WHO classification undergoing tumor resection. Clinical, histopathological and imaging findings were collected and correlated with preoperative seizure development. Tumor and edema volumes were quantified.ResultsNinety-five patients with a mean age of 59.5 ± 16.0 years were included. Most tumors (86/95, 90.5%) were classified as atypical meningioma WHO grade 2. Nine of 95 tumors (9.5%) corresponded to anaplastic meningiomas WHO grade 3, including six patients harboring TERT promoter mutations. Meningiomas were most frequently located at the convexity in 38/95 patients (40.0%). Twenty-eight of 95 patients (29.5%) experienced preoperative seizures. Peritumoral edema was detected in 62/95 patients (65.3%) with a median volume of 9 cm3 (IR: 0–54 cm3). Presence of peritumoral edema but not age, tumor localization, TERT promoter mutation, brain invasion or WHO grading was associated with incidence of preoperative seizures, as confirmed in multivariate analysis (OR: 6.61, 95% CI: 1.18, 58.12, p = *0.049). Postoperative freedom of seizures was achieved in 91/95 patients (95.8%).ConclusionsPreoperative seizures were frequently encountered in about every third patient with meningioma WHO grade 2 or 3. Patients presenting with peritumoral edema on preoperative imaging are at particular risk for developing tumor-related seizures. Tumor resection was highly effective in achieving seizure freedom.

Breast edema score at breast MRI: its value in prediction of molecular subtype of breast cancer and its impact on axillary LN metastasis

BackgroundSince many newly diagnosed breast cancer patients have breast MRI, the value of preoperative breast magnetic resonance imaging would improve if molecular subtypes could be consistently identified, and prognostic information provided in addition to diagnostic imaging. Breast edema may improve the ability to predict molecular subtypes and clinical and pathological outcomes in invasive breast cancer patients. The prognosis for breast cancer prognosis based on the findings of breast edema by magnetic resonance imaging will be useful in both pretreatment planning and prognosis. Breast edema on T2-weighted images and STIR was scored on a scale of 1 to 4, as follows: (a) breast edema score (BES) 1, no edema; (b) BES 2, peritumoral edema; (c) BES 3, pre pectoral edema; and (d) BES 4, subcutaneous edema (suspicious for occult inflammatory breast cancer “IBC”). Axillary lymph node status and number were also evaluated in T2 and STIR and after contrast administration. The aim of this work was to assess the role of tumour-related breast edema MRI features in distinguishing molecular subtypes of breast cancer and its effect on pathological axillary lymph nodes in patients with breast cancer.ResultsThere was a highly significant difference between BES with respect to the molecular subtypes of breast cancer, size of the mass, Ki-67 expression, LN status, and LN number (p < 0.0001, 0.045, < 0.0001, < 0.0001, and < 0.0001 respectively). However, there was no significant difference between BES and histopathological grade in studied masses, such as p-value = 0.49.ConclusionsTumour-related breast edema MRI characteristics may be useful in distinguishing molecular subtypes of breast cancer and could be used as a promising feature to improve the predictive performance of pathological axillary lymph nodes in patients with breast cancer, contributing to preoperative treatment planning and prognostic outcome.

Impact of glioma peritumoral edema, tumor size, and tumor location on alternating electric fields (AEF) therapy in realistic 3D rat glioma models: a computational study

Objective. Alternating electric fields (AEF) therapy is a treatment modality for patients with glioblastoma. Tumor characteristics such as size, location, and extent of peritumoral edema may affect the AEF strength and distribution. We evaluated the sensitivity of the AEFs in a realistic 3D rat glioma model with respect to these properties. Approach. The electric properties of the peritumoral edema were varied based on calculated and literature-reported values. Models with different tumor composition, size, and location were created. The resulting AEFs were evaluated in 3D rat glioma models. Main results. In all cases, a pair of 5 mm diameter electrodes induced an average field strength >1 V cm−1. The simulation results showed that a negative relationship between edema conductivity and field strength was found. As the tumor core size was increased, the average field strength increased while the fraction of the shell achieving >1.5 V cm−1 decreased. Increasing peritumoral edema thickness decreased the shell's mean field strength. Compared to rostrally/caudally, shifting the tumor location laterally/medially and ventrally (with respect to the electrodes) caused higher deviation in field strength. Significance. This study identifies tumor properties that are key drivers influencing AEF strength and distribution. The findings might be potential preclinical implications.

Case Report and Literature review. Neuropsychiatry Manifestation of Frontal Lobe Neoplasm- Meningioma. Prevalence, Presentation and Pathogenesis

IntroductionMeningiomas are the most frequent primary brain tumor. Although most Meningiomas are benign, their location in the central nervous system can predict symptomatology which could result in significant morbidity and mortality. However, due to the slow-growing nature, meningiomas are usually asymptomatic, and diagnosis is often made incidentally on neuroimaging or at an autopsy. The incidence rate is 1.2-fold higher in Black Americans than White Americans. Neuropsychiatry manifestation might be only initial presentation; thus, psychiatrists are often the first to see these patients, and the correct diagnosis may be made only when the tumor has grown to a considerable size and begun to displace the brain.ObjectivesThe aim of this study is to understand the biological basis of psychiatry symptoms in patients with Frontal Lobe meningiomas.MethodsA review of literature and individual patient data analysis was conducted. The literature review was conducted on PubMed, Medline, MeSH, Google Scholar, and mount Sinai’s levy Library using the key words; meningioma, meningioma with psychiatric symptoms, psychosis, depression, neuropsychiatry manifestation of meningiomas.ResultsThe review revealed that 88% of brain tumors and psychiatric symptoms are located in the frontal region. Meningiomas accounts for 13%-26% of intracranial tumors. There is a reported low incidence due to its slow growing nature and are usually asymptomatic. Incidence of meningiomas is predominant in females, and is attributed to hormonal factors, this is associated with estrogen and progestogen cycles. Reports shows that smoking has been linked to increase risk of meningiomas in men. Frontal lobe meningiomas may present with only psychological symptoms that resemble depression, anxiety states, hypomania and schizophrenia. Personality and mental status changes are also noted in Frontal lobe tumors. Left sided lesions are associated with inhibition of motor activity, impairment in motor and initiative aspect of speech, diminished generalization ability and general inertia of mental process.Conclusions Given the absence of frank neurological symptoms, to help localize the lesion, most meningiomas are missed due to diagnostic overshadowing of the primary psychiatric illness. Peritumoral edema indicates the underlying mechanism and location of the lesion predicts symptomatology. Like our patient who is an 81-year-old male with no past psychiatry history, presenting to our comprehensive psychiatry emergency program with psychiatric manifestation as the initial presentation and subsequently with MRI suggestive of Right Frontal extra-axial meningioma. This study shows that primitive frontal lobe tumors are likely to be misdiagnosed as patients with such tumors are often referred first to psychiatrist. High index of suspicious is needed.Disclosure of InterestNone Declared

Improvement of diffusion tensor imaging-based tractography by free-water correction in nonedematous gliomas: assessment with brain mapping.

The free-water correction algorithm (Freewater Estimator Using Interpolated Initialization [FERNET]) can be applied to standard diffusion tensor imaging (DTI) tractography to improve visualization of subcortical bundles in the peritumoral area of highly edematous brain tumors. Interest in its use for presurgical planning in purely infiltrative gliomas without peritumoral edema has never been evaluated. Using subcortical maps obtained with direct electrostimulation (DES) in awake surgery as a reference standard, the authors sought to 1) assess the accuracy of preoperative DTI-based tractography with FERNET in a series of nonedematous glioma patients, and 2) determine its potential usefulness in presurgical planning. Based on DES-induced functional disturbances and tumor topography, the authors retrospectively reconstructed the putatively stimulated bundles and the peritumoral tracts of interest (various associative and projection pathways) of 12 patients. The tractography data obtained with and without FERNET were compared. The authors identified 21 putative tracts from 24 stimulation sites and reconstituted 49 tracts of interest. The number of streamlines of the putative tracts crossing the DES area was 26.8% higher (96.04 vs 75.75, p = 0.016) and their volume 20.4% higher (13.99 cm3 vs 11.62 cm3, p < 0.0001) with FERNET than with standard DTI. Additionally, the volume of the tracts of interest was 22.1% higher (9.69 cm3 vs 7.93 cm3, p < 0.0001). Free-water correction significantly increased the anatomical plausibility of the stimulated fascicles and the volume of tracts of interest in the peritumoral area of purely infiltrative nonedematous gliomas. Because of the functional importance of the peritumoral zone, applying FERNET to DTI could have potential implications on surgical planning and the safety of glioma resection.

Recurrence and Mortality Rate in a 42 Patient Cohort of Giant Meningiomas

BackgroundGiant meningiomas may show special features in terms of biological behavior and management. We aimed to research recurrence and mortality of giant meningiomas. MethodsMedical files of patients with meningioma with at least one dimension of ≥5 cm in any plane in radiological investigations between December 2012 and January 2022 were retrospectively reviewed. Tumor dimensions were measured on magnetic resonance images except one. All patients except two underwent clinical follow-up at a mean of 27.19 ± 29.87 (range, 4–112) months. ResultsThere were 42 patients, 26 (61.9%) women and 16 (38.1%) men who ranged in age from 31 to 85 (mean, 60.31 ± 14.86) years. Headache (57.1%) was the most common symptom. The mean tumor size was 70.14 ± 19.03 (range, 50–152) mm. Tumors were most located at the frontal convexity (40.5%). Simpson grade I resection was achieved in 19% of the cases. The tumors were World Health Organization (WHO) grade 1 in 74% and grade 2 in 26% of the cases. Major complications developed in 26.1% of the patients. Recurrence happened in 5 (11.9%) cases. The number of WHO grade 2 tumors (p = 0.013; p<0.05) and tumor size (p = 0.006; p<0.01) were significantly higher in the recurrent cases. Mortality was % 11.9 and statistically significantly higher in the recurrence group (p = 0.025; p<0.05). ConclusionGiant intracranial meningiomas are challenging because of surgical experience, tumor size, peritumoral edema, blood supply, anatomical changes, and limited visibility. They have a high risk of recurrence and mortality.

Susceptibility-Weighted MRI for Predicting NF-2 Mutations and S100 Protein Expression in Meningiomas.

S100 protein expression levels and neurofibromatosis type 2 (NF-2) mutations result in different disease courses in meningiomas. This study aimed to investigate non-invasive biomarkers of NF-2 copy number loss and S100 protein expression in meningiomas using morphological, radiomics, and deep learning-based features of susceptibility-weighted MRI (SWI). This retrospective study included 99 patients with S100 protein expression data and 92 patients with NF-2 copy number loss information. Preoperative cranial MRI was conducted using a 3T clinical MR scanner. Tumor volumes were segmented on fluid-attenuated inversion recovery (FLAIR) and subsequent registration of FLAIR to high-resolution SWI was performed. First-order textural features of SWI were extracted and assessed using Pyradiomics. Morphological features, including the tumor growth pattern, peritumoral edema, sinus invasion, hyperostosis, bone destruction, and intratumoral calcification, were semi-quantitatively assessed. Mann-Whitney U tests were utilized to assess the differences in the SWI features of meningiomas with and without S100 protein expression or NF-2 copy number loss. A logistic regression analysis was used to examine the relationship between these features and the respective subgroups. Additionally, a convolutional neural network (CNN) was used to extract hierarchical features of SWI, which were subsequently employed in a light gradient boosting machine classifier to predict the NF-2 copy number loss and S100 protein expression. NF-2 copy number loss was associated with a higher risk of developing high-grade tumors. Additionally, elevated signal intensity and a decrease in entropy within the tumoral region on SWI were observed in meningiomas with S100 protein expression. On the other hand, NF-2 copy number loss was associated with lower SWI signal intensity, a growth pattern described as "en plaque", and the presence of calcification within the tumor. The logistic regression model achieved an accuracy of 0.59 for predicting NF-2 copy number loss and an accuracy of 0.70 for identifying S100 protein expression. Deep learning features demonstrated a strong predictive capability for S100 protein expression (AUC = 0.85 ± 0.06) and had reasonable success in identifying NF-2 copy number loss (AUC = 0.74 ± 0.05). In conclusion, SWI showed promise in identifying NF-2 copy number loss and S100 protein expression by revealing neovascularization and microcalcification characteristics in meningiomas.

High-performance presurgical differentiation of glioblastoma and metastasis by means of multiparametric neurite orientation dispersion and density imaging (NODDI) radiomics

ObjectivesTo evaluate the performance of multiparametric neurite orientation dispersion and density imaging (NODDI) radiomics in distinguishing between glioblastoma (Gb) and solitary brain metastasis (SBM).Materials and methodsIn this retrospective study, NODDI images were curated from 109 patients with Gb (n = 57) or SBM (n = 52). Automatically segmented multiple volumes of interest (VOIs) encompassed the main tumor regions, including necrosis, solid tumor, and peritumoral edema. Radiomics features were extracted for each main tumor region, using three NODDI parameter maps. Radiomics models were developed based on these three NODDI parameter maps and their amalgamation to differentiate between Gb and SBM. Additionally, radiomics models were constructed based on morphological magnetic resonance imaging (MRI) and diffusion imaging (diffusion-weighted imaging [DWI]; diffusion tensor imaging [DTI]) for performance comparison.ResultsThe validation dataset results revealed that the performance of a single NODDI parameter map model was inferior to that of the combined NODDI model. In the necrotic regions, the combined NODDI radiomics model exhibited less than ideal discriminative capabilities (area under the receiver operating characteristic curve [AUC] = 0.701). For peritumoral edema regions, the combined NODDI radiomics model achieved a moderate level of discrimination (AUC = 0.820). Within the solid tumor regions, the combined NODDI radiomics model demonstrated superior performance (AUC = 0.904), surpassing the models of other VOIs. The comparison results demonstrated that the NODDI model was better than the DWI and DTI models, while those of the morphological MRI and NODDI models were similar.ConclusionThe NODDI radiomics model showed promising performance for preoperative discrimination between Gb and SBM.Clinical relevance statementThe NODDI radiomics model showed promising performance for preoperative discrimination between Gb and SBM, and radiomics features can be incorporated into the multidimensional phenotypic features that describe tumor heterogeneity.Key Points• The neurite orientation dispersion and density imaging (NODDI) radiomics model showed promising performance for preoperative discrimination between glioblastoma and solitary brain metastasis.• Compared with other tumor volumes of interest, the NODDI radiomics model based on solid tumor regions performed best in distinguishing the two types of tumors.• The performance of the single-parameter NODDI model was inferior to that of the combined-parameter NODDI model.

Prediction of Lymphovascular invasion status in breast cancer based on magnetic resonance imaging radiomics features

ObjectiveThis study intended to investigate the feasibility and effectiveness of using clinical magnetic resonance imaging (MRI) radiomics features to predict lymphovascular invasion (LVI) status in breast cancer (BC) patients. MethodsA total of 182 BC patients were retrospectively collected and randomly divided into a training set (n = 127) and a validation set (n = 55) in a 7:3 ratio. Based on pathological examination results, the training set was further divided into LVI group (n = 60) and non-LVI group (n = 67), and the validation set was divided into LVI group (n = 24) and non-LVI group (n = 31). General data and MRI examination indicators were compared. Multivariate logistic regression was utilized to analyze MRI radiomics features and clinically relevant indicators that were significant in the baseline information of patients in training set, independent risk factors were identified, and a logistic regression model was built. The accuracy of logistic model was validated using ROC curves in training and validation sets. ResultsAge, pathohistological classification, tumor length, tumor width, presence or absence of Magnetic Resonance Spectroscopy (MRS) cho peak, presence or absence of spicule sign, peritumoral enhancement, and peritumoral edema were statistically significant (P < 0.05) between the two groups. Multivariate logistic regression analysis presented that spicule and peritumoral edema were independent risk factors for LVI in BC patients (P < 0.05). The ROC curve illustrated that AUC of the logistic regression model in the training set was 0.807 (95%CI: 0.730–0.885) and that in the validation set was 0.837 (95%CI: 0.731–0.944). ConclusionRadiomics features of spicule sign and peritumoral edema were independent risk factors for LVI in BC patients. A logistic regression model based on these factors, along with age, could accurately predict LVI occurrence in BC patients, providing data support for diagnosis and modeling of LVI in BC patients.

Assessment of magnetic resonance imaging and histopathological changes in chordoid glioma: A retrospective analysis of 13 cases

AbstractChordoid glioma (CG) is a rare tumor, and its predominantly anterior location is in the third ventricle. However, the clinical characteristics of CG were not obvious, and there was less knowledge of CG‐related imaging. This study aimed at exploring the MRI imaging features of CG. We retrospectively analyzed the MRI data of 13 patients diagnosed with CG from January 2015 to May 2021. The pathological change of tumor tissue was observed using H&amp;E staining and immunohistochemical. The MRI manifestations of CG often include phyllode masses in the anterior part of the third ventricle. T2WI is dominated by iso‐ and hypointensity, with internal patchy hyperintensity, marked enhancement, and peritumoral edema. The “eight‐character edema sign” runs along the optic beam and may be useful for distinguishing CG from other tumors. CG has unique MRI manifestations that can serve as a diagnostic basis. Our study may help to enhance the understanding of imaging about CG and improve the diagnosis of patients with CG.

High Peritumoral and Intratumoral T2 Signal Intensity in HER2-Positive Breast Cancers on Preneoadjuvant Breast MRI: Assessment of Associations With Histopathologic Characteristics.

BACKGROUND. Intratumoral necrosis and peritumoral edema are features of aggressive breast cancer that may present as high T2 signal intensity (T2 SI). Implications of high T2 SI in HER2-positive cancers are unclear. OBJECTIVE. The purpose of this study was to assess associations with histopathologic characteristics of high peritumoral T2 SI and intratumoral T2 SI of HER2-positive breast cancer on MRI performed before initiation of neoadjuvant therapy. METHODS. This retrospective study included 210 patients (age, 24-82 years) with 211 HER2 breast cancers who, from January 1, 2015, to July 30, 2022, underwent breast MRI before receiving neoadjuvant therapy. Two radiologists independently assessed cancers for high peritumoral T2 SI and high intratumoral T2 SI on fat-suppressed T2-weighted imaging and classified patterns of high peritumoral T2 SI (adjacent to tumor vs prepectoral extension). A third radiologist resolved discrepancies. Multivariable logistic regression analyses were performed to identify associations of high peritumoral and intratumoral T2 SI with histopathologic characteristics (associated ductal carcinoma in situ, hormone receptor status, histologic grade, lymphovascular invasion, and axillary lymph node metastasis). RESULTS. Of 211 HER2-positive cancers, 81 (38.4%) had high peritumoral T2 SI, and 95 (45.0%) had high intratumoral T2 SI. A histologic grade of 3 was independently associated with high peritumoral T2 SI (OR = 1.90; p = .04). Otherwise, none of the five assessed histopathologic characteristics were independently associated with high intratumoral T2 SI or high peritumoral T2 SI (p > .05). Cancers with high T2 SI adjacent to the tumor (n = 29) and cancers with high T2 SI with prepectoral extension (n = 52) showed no significant difference in frequency for any of the histopathologic characteristics (p > .05). Sensitivities and specificities for predicting the histopathologic characteristics ranged from 35.6% to 43.7% and from 59.7% to 70.7%, respectively, for high peritumoral T2 SI, and from 37.3% to 49.6% and from 49.3% to 62.7%, respectively, for high intratumoral T2 SI. Interreader agreement was almost perfect for high peritumoral T2 SI (Gwet agreement coefficient [AC] = 0.93), high intratumoral T2 SI (Gwet AC = 0.89), and a pattern of high peritumoral T2 SI (Gwet AC = 0.95). CONCLUSION. The only independent association between histopathologic characteristics and high T2 SI of HER2-positive breast cancer was observed between a histologic grade of 3 and high peritumoral T2 SI. CLINICAL IMPACT. In contrast with previously reported findings in broader breast cancer subtypes, peritumoral and intratumoral T2 SI had overall limited utility as prognostic markers of HER2-positive breast cancer.

A large open access dataset of brain metastasis 3D segmentations on MRI with clinical and imaging information

Resection and whole brain radiotherapy (WBRT) are standard treatments for brain metastases (BM) but are associated with cognitive side effects. Stereotactic radiosurgery (SRS) uses a targeted approach with less side effects than WBRT. SRS requires precise identification and delineation of BM. While artificial intelligence (AI) algorithms have been developed for this, their clinical adoption is limited due to poor model performance in the clinical setting. The limitations of algorithms are often due to the quality of datasets used for training the AI network. The purpose of this study was to create a large, heterogenous, annotated BM dataset for training and validation of AI models. We present a BM dataset of 200 patients with pretreatment T1, T1 post-contrast, T2, and FLAIR MR images. The dataset includes contrast-enhancing and necrotic 3D segmentations on T1 post-contrast and peritumoral edema 3D segmentations on FLAIR. Our dataset contains 975 contrast-enhancing lesions, many of which are sub centimeter, along with clinical and imaging information. We used a streamlined approach to database-building through a PACS-integrated segmentation workflow.