Literatura académica sobre el tema "Peritumoral area"

Peritumoral areas or microenvironments surrounding melanoma are unexplored and partially understood, so that, in the following paper, an algorithm that predicts the trend of the melanoma progression is proposed. Additionally, in case of melanoma the peritumoral area is significantly correlated with the texture that belongs inside the skin lesion. The proposed algorithm analyses the region of interest (ROI) with Normalized 2-D cross-correlation (NCC) method and predicts the pattern in the peritumoral area which is most similar with the texture of the melanoma. An important step is the detection of the peritumoral area, in which case, the mathematical morphology techniques were proposed. The verifying of similarity between the samples cropped from inside the melanoma and peritumoral area with Structural Similarity Index (SSIM) was performed. The main advantage of the proposed algorithm is that it can be applied on different medical image types and tumors. The algorithm was tested on two datasets 7-Point and PH2, and two computes.

2050 Background: The infiltrating nature of gliomas, particularly into the peritumoral area, is a major barrier to improving clinical outcome as microscopic disease remains even after apparent gross total resection. Conventional T1 post-contrast and T2/FLAIR MRI do not capture full tumor extent. A better imaging biomarker is needed to improve differentiation between tumor, peritumoral area and normal brain. Methods: 4 pre-surgical patients with non-enhancing, FLAIR-hyperintense lesions suspicious for glioma underwent ultra-high gradient diffusion MRI on the Connectome MRI scanner, a unique scanner with maximum gradient strength of 300 mT/m enabling mapping of cellular microstructures on a micron-level scale. The FLAIR area was defined as the tumor region of interest (ROI). Radiographically normal appearing brain up to 1 cm around the FLAIR area was defined as the peritumoral ROI. Using a novel 3 compartment diffusion model (Linear Multiscale Model), the volume fraction of water (VFW) was calculated within restricted (intracellular), hindered (extracellular) and free (CSF) spaces. VFW in the tumor, peritumoral ROI, contralateral normal white matter (WM) and cortex were compared. Results: Within the tumor ROI, the median VFW in the restricted compartment was decreased vs. the peritumoral ROI (↓ 34%), WM (↓ 46%) and cortex (↓ 18%) while median VFW in the hindered compartment was increased vs. the peritumoral ROI (↑ 26%), WM (↑ 54%) and cortex (↑ 25%). Within the peritumoral ROI, median VFW in the hindered compartment was increased compared to WM (↑ 23%). 3 patients had available histopathology revealing isocitrate dehydrogenase-mutant gliomas. Conclusions: Using ultra-high gradient diffusion MRI and a novel diffusion model, we detected distinct diffusion patterns in the tumor and peritumoral area not seen on conventional MRI. Lower VFW in the restricted compartment within the tumor may reflect decreased intracellular water mobility due to enlarged nuclei. Higher VFW in the hindered compartment in the tumor and peritumoral area may reflect higher degree of tissue permeability and edema. MRI-pathology and larger cohort validation studies are underway to elucidate microenvironment changes in response to treatment.

BACKGROUND: Primary malignant brain tumor and metastases on the brain have a similar pattern in conventional Magnetic Resonance Imaging (MRI), even though both require entirely different treatment and management. The pathophysiological difference of peritumoral edema can help to distinguish the case of primary malignant brain tumor and brain metastases. AIM: This study aimed to analyze the ratio of the area of peritumoral edema to the tumor using Otsu’s method of image segmentation technique with a user-friendly Graphical User Interface (GUI). METODS: Data was prepared by obtaining the examination results of Anatomical Pathology and MRI imaging. The area of peritumoral edema was identified from MRI image segmentation with T2/FLAIR sequence. While the area of tumor was identified using MRI image segmentation with T1 sequence. RESULTS: The Mann-Whitney test was employed to analyze the ratio of the area of peritumoral edema to tumor on both groups. Data testing produced a significance level of 0.013 (p < 0.05) with a median value (Nmax-Nmin) of 1.14 (3.31-0.08) for the primary malignant brain tumor group and a median value (Nmax-Nmin) of 1.17 (10.30-0.90) for the brain metastases group. CONCLUSIONS: There was a significant difference in the ratio of the area of peritumoral edema to the area of tumor from both groups, in which brain metastases have a greater value than the primary malignant brain tumor.

Abstract Blood flow was measured in intratumoral tissue, the cerebral hemispheres and particularly in the peritumoral area of 12 patients with intracranial meningiomas using the stable xenon-enhanced computed tomographic scan. Tumor blood flow frequently showed a heterogeneous pattern of enhancement with high flow at the tumor periphery and a central area of hypoperfusion. Blood flow values were on average 28% lower in the peritumoral area than in the ipsilateral cerebral hemisphere. In individual cases, blood flow values in the peritumoral edematous area were very low. These findings suggest that the hypodense area surrounding meningiomas does not solely represent vasogenic edema, but may actually represent tumor pressure ischemia.

Object Peritumoral seizures are an early symptom of a glioma. To gain a better understanding of the molecular mechanism underlying tumor-induced epileptogenesis, the authors studied modulation of the N-methyl-d-aspartate (NMDA) receptor in peritumoral tissue. Methods To study the possible etiology of peritumoral seizures, NMDA receptor expression, posttranslational modification, and function were analyzed in an orthotopic mouse model of human gliomas and primary patient glioma tissue in which the peritumoral border (tumor-brain interface) was preserved in a tissue block during surgery. Results The authors found that the NMDA receptor containing the 2B subunit (NR2B), a predominantly extrasynaptic receptor, is highly phosphorylated at S1013 in the neurons located in the periglioma area of the mouse brain. NR2B is also highly phosphorylated at S1013 in the neurons located in the peritumoral area from human brain tissue containing a glioma. The phosphorylation of the extrasynaptic NMDA receptor increases its permeability for Ca2+ influx and subsequently mediates neuronal overexcitation and seizure activity. Conclusions These data suggest that overexcitation of the extrasynaptic NMDA receptors in the peritumoral neurons may contribute to the development of peritumoral seizures and that the phosphorylated NR2B may be a therapeutic target for blocking primary brain tumor–induced peritumoral seizures.

ABSTRACT Purpose: We evaluated the potential role of intravoxel incoherent motion (IVIM) in predicting the therapeutic response and peritumoral invasion in patients with hepatocellular carcinoma (HCC) treated with transarterial chemoembolization (TACE). Materials and Methods: We enrolled 47 patients previously treated with TACE between January 2018 and December 2021. We evaluated the IVIM-derived metrics [apparent diffusion coefficient (ADC), D, D*, f] in the TACE-treated, peritumoral, and parenchymal areas of the liver. Results: The ADCtace and Dtace values (1.13 ± 0.22 × 10−3 m2/s vs 0.95 ± 0.13 × 10−3 mm2/s, 1.28 ± 0.27 × 10−3 mm2/s vs 1.07 ± 0.3 × 10−3 mm2/s, P < 0.05) were higher in the non-progressing groups than in the progressing groups in the TACE-treated areas. Dpt represented the D values in the peritumoral area, which can distinguish between the progressive and non-progressive groups with an AUC of 0.73. The Dstd values, which represent the D values in the peritumoral area normalized by the D values in the liver parenchyma in the non-progressing groups (1.10 ± 0.14 × 10−3 mm2/s), were higher than those of the progressing groups (0.93 ± 0.17 × 10−3 mm2/s). Conclusion: The ADCtace, Dtace, Dpt, and Dstd values reflect the changes in the microstructure of the progressive and non-progressive groups after TACE treatment, showing robust diagnostic performances in predicting the therapeutic response and peritumoral invasion.

The aim of the study was to study and evaluate the predictive value of the immune microenvironment of gastric cancer and morphologically normal mucous membrane of the peritumoral area using an automatic morphometric analysis system on the example of CD 8+ cells.Material and Methods. Surgical samples from 130 patients with a verified diagnosis of gastric cancer were used. After immunohistochemical staining with antibodies to CD 8, a morphological assessment was performed according to the original method. We assessed the average area of CD 8+ cells in three fields of view (lens magn. ×20) using the automatic system of morphometric analysis LAS X (Leica) in the central part of the tumor and areas of morphologically normal mucous membrane of the peritumoral region directly adjacent to the tumor tissue. The results were compared with the main clinical and morphological characteristics of the tumor as well as with the overall five-year survival of patients.Results and Discussion. A high density of CD 8+ infiltration of normal mucous membrane of the peritumoral area was observed in groups T4a and T4b by the depth of invasion (n=96, p=0.0089) and was associated with the presence of emboli in the lymphatic vessels (n=96, p=0.0102) and with the more advanced stage of gastric cancer (n=96, p=0.0107). The studied cases were divided into two groups: less than 3300 square micrometers (better patient survival; n=79, p=0.01) and more than 3300 square micrometers according to the average area of CD 8+ cells in normal mucous membrane of the peritumoral area. According to multivariate survival analysis using the Cox regression model, it was found that the average area of CD 8+ cells in normal mucous membrane of the peritumoral area was a significant negative prognostic factor (RR=1.537; CI : 0.761–3.105; p<0.01) comparable in degree covariance with the stage of the tumor A similar indicator assessed in central part of the tumor was not significantly associated with patient survival (RR=0.803; CI : 0.574–1.122; p>0.05).Conclusion. The possibility of using an automatic analysis system to evaluate the immune microenvironment in gastric cancer was demonstrated for the first time. It was found that a high level of CD 8+ lymphocyte infiltration of morphologically normal mucous membrane of the peritumoral area was an independent negative prognostic factor. Therefore, we recommend the mandatory preoperative biopsy sampling from the mucous membrane of the peritumoral region for morphometric assessment of CD 8+ lymphocyte infiltration.

Background and Objectives: Even if they are cells of controversial origin (mesenchymal, perivascular, or fibroblastic), follicular dendritic cells (FDC) are present in all organs. The aim of this study was to establish the FDC expression pattern and its interrelation with HPV 18 expression in laryngeal squamous cell carcinoma (LSCC). Materials and Methods: Fifty-six cases of LSCC were evaluated by simple and double immunostaining. The following score was used: 0 (negative or few positive cells), 1 (10–30% of positive cells), 2 (30–50% of cells), and 3 (over 50% of cells). Results: The expression of CD 21-positive cells with dendritic morphology (CDM) was noticed in the intratumoral area of conventional (well and poorly differentiated types and HPV 18 positive cases with a value of 2 for the score) and papillary types (HPV-18 negative cases with a score of 1). The highest value of 2 for the score of CDM in HPV-18 positive cases was found in the peritumoral area of well- and poorly-differentiated conventional LSCCs. A significant correlation was found between scores of CDM from the intratumoral area and those of the peritumoral area (p = 0.001), between CDM and non-dendritic morphology cells (NDM) of the intratumoral area (p = 0.001), and between HPV-18 status and peritumoral NDM cells (p = 0.044). Conclusions: The FDC and NDM cell score values of intratumoral and peritumoral areas may represent important parameters of LSCCs. This may contribute to a better stratification of laryngeal carcinoma cases and the individualized selection of clinical treatment protocols.

Abstract Background: We previously demonstrated that the analysis of the tumor microenvironment (TME) in histopathology images via tissue segmentation [1] and cell density in lymphocyte-rich area [2] impacts prognosis and treatment in hepatocellular carcinoma (HCC). Few biomarker models exist to prognosticate patients with HCC via the automated analysis of TME at the cellular level. Methods: Clinical outcomes data and histopathology images of 351 patients with HCC were obtained from TCGA. We advanced a deep learning-based algorithm to analyze the tumor volume and spatial distribution of nuclei in TME. This was based on combination of two models: the PAIP2019 dataset was used for DenseNet-based HCC segmentation, which showed the performance of 0.8582 on the F1-score metric [3]; HoverNet-based cell detection model, which showed the performance of 0.654 on the binary PQ metric, annotated lymphocytes, macrophages, and neutrophils on the MonuSac dataset [4]. Results: The HCC segmentation model divided the TME into tumoral, marginal, and peritumoral areas by image processing. The marginal and peritumoral areas were defined as inner 50 um area and outer 100 um area from the estimated tumoral boundary, respectively. The ratios of neutrophils, lymphocytes, macrophages to the total cell count on marginal and peritumoral areas were calculated through integration of HCC segmentation and cell detection models. The proportions of leukocytes were subjected into Cox proportional hazard analysis. The results of Cox proportional hazard analysis calculated the proportions of macrophages and lymphocytes to other cells in the TME. The macrophage proportion on the peritumoral area was a significant prognostic indicator showing Log(hazard ratio) (-2.42 ± 2.14, p=0.026). The lymphocyte proportion on both areas of the peritumor and margins showed significant Log(hazard ratio) (-1.70 ± 1.61, p=0.042). Conclusions: The retrospective analysis of the TME using deep learning-assisted algorithm combining tissue segmentation and cell detection models reveals that the ratio of lymphocytes and macrophages in the peri-tumoral areas of HCC TME significantly impact prognosis. Further analyses in the prospective studies may provide more information about cellular biomarkers. [1] Kim et al. Cancer Res 2020 (80) (16 Supp) 2631 [2] Park et al. Journal of Clinical Oncology 39, no. 15_suppl (May 20, 2021) 4107-4107 [3] Kim, Yoo Jung, Jang, Hyungjoon, Lee, Kyoungbun et al. Medical Image Analysis 67 (2021): 101854. [4] Verma, Ruchika. IEEE Transactions on Medical Imaging 39 (2020): 1380-1391. [5] Graham, Simon. Medical Image Analysis 58 (2019): 101563. Citation Format: Hongseok Lee, Kyungdoc Kim, Guhyun Kang, Kyu-Hwan Jung, Sunyoung S. Lee. Spatial distribution of immune cells as quantitative prognosis indicator in hepatocellular carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1721.

Abstract PURPOSE The differential diagnosis of glioblastoma (GBM) versus single brain metastasis (Met) is clinically important, and is undertaken with a clinical reading of MR images and/or tumor biopsy. We investigate whether Mets and GBMs can be differentiated based on the microstructure of the FLAIR-hyperintense peritumoral region measured by diffusion tensor imaging (DTI). We hypothesize that the peritumoral microstructure differs in extracellular water content, based on whether it is vasogenic edema or infiltrative. We use deep learning trained on DTI-based free-water volume fraction maps to discriminate between the peritumoral regions of Met and GBM neoplasms. Our results are also compared with mean diffusivity (MD), the most commonly used DTI metric. METHOD dMRI data of 143 patients with brain tumors (89 glioblastomas and 54 metastases, ages 19-87 years, 77 females and 66 males) were included. Free-water volume fraction maps were computed for the peritumoral regions (demarcated automatically). We developed a 7-layer convolutional neural network (CNN) architecture to distinguish microstructural patterns of Met and GBM tumors using 32 x 32 mm patches placed at random in the peritumoral area. The CNN was trained on patches from a training set of 113 patients and tested on the remaining 30 patients, where majority voting was applied to predict the tumor type for each patient. Although MD has been previously used in both tumor and peritumoral area for discriminating tumor type, we replicated the same process with MD only in the peritumoral area to provide a stronger comparison. RESULT We predicted tumor type with 93% accuracy, outperforming MD with 84% accuracy. CONCLUSION Our results demonstrate that deep learning with CNN on DTI-based free-water volume fraction map can be a promising tool for automatic distinction of tumor types, and has potential as a tumor biomarker.

Les sarcomes sont des tumeurs conjonctives malignes rares et représentent 2/100.000 nouveaux cas par an. Il s’agit d’un groupe hétérogène de tumeurs, généralement de mauvais pronostic. La chirurgie reste à ce jour le seul traitement curatif. Ces tumeurs peuvent récidiver même après une chirurgie considérée comme optimale, classée R0 c’est à dire sans reliquat microscopique (dans environ 10% des cas). Différents facteurs anatomocliniques pronostiques de rechute sont identifiés, incluant la taille tumorale initiale, le grade histologique FNCLCC et la localisation tumorale profonde. A l’heure actuelle, on ne dispose d’aucun marqueur prédictif du risque individuel de récidive au décours d’une prise en charge chirurgicale curative de sarcome. L’identification de facteurs prédictifs de rechute permettrait de mieux cibler les traitements adjuvants sur les patients à haut risque de rechute et de proposer une surveillance radio-clinique accrue.Jusqu’ici, les études se sont concentrées sur les caractéristiques des cellules tumorales mais n’ont jamais pris en compte les marges tissulaires. La marge constitue l’interface entre le tissu tumoral et le tissu sain, il s’agit d’un tissu remanié situé au contact direct des cellules tumorales. Le mode d’infiltration des cellules tumorales diffère d’une tumeur à l’autre et pourrait moduler ou refléter le risque de rechute locale. Une signature moléculaire de tissu sain prédictive de rechute locale a ainsi été mise en évidence dans le carcinome hépatocellulaire mais aucune donnée n’est disponible dans les sarcomes. Mon projet de thèse vise à identifier des facteurs prédictifs de rechute tumorale locale en étudiant de façon systématique et comparative la tumeur et ses zones périphériques, incluant la zone tumorale centrale (Tc), zone tumorale périphérique (Tp), le tissu péritumoral sain au contact des cellules tumorales (TS-R1) et le tissu sain à distance (TS) dans une série rétrospective de 144 sarcomes des tissus mous.Le premier volet a caractérisé l’infiltrat immunitaire associé aux sarcomes en étudiant systématiquement la marge tissulaire avec un focus sur les structures lymphoïdes tertiaires (TLS), facteurs prédictifs de réponse à l’immunothérapie dans les sarcomes à l’aide d’une étude microscopique et immunohistochimique des prélèvements. La distribution des TLS prédomine dans la marge tumorale et semble être corrélée à un meilleur pronostic.Le second volet a étudié par deep learning (DL) les différentes zones tumorales à l’aide de lames scannées afin de mettre en évidence de nouveaux facteurs morphologiques prédictifs inconnus et une signature DL prédictive de rechute locale. Le score du DL dépasse les courbes de survie associées au grade FNCLCC, standard utilisée en clinique.Une 3e approche a comparé le transcriptome des différentes zones tumorales déterminé par whole RNA-sequencing afin d’identifier des biomarqueurs dérégulés de façon différentielles dans les différentes zones et de déterminer les signatures immunologiques entre les différents territoires. Des gènes d’intérêt ont été mis en évidence dans la zone marginale pouvant être associé au risque de rechute. Enfin une analyse spatiale transcriptomique par technique Visium a été réalisée sur quelques cas à titre exploratoire.Notre étude a ciblé des biomarqueurs corrélés au risque de rechute qui pourraient permettre à l’avenir d’identifier les patients à haut risque de rechute afin de personnaliser leur suivi et valider des modalités thérapeutiques complémentaires
Identification of morphological and molecular predictive factors of recurrence in soft tissue sarcomas of the limbs and trunk wallSarcomas are rare malignant mesenchymal tumors that represent 2/100,000 new cases per year. They represent a heterogeneous group of tumors, generally associated with a poor prognosis. Surgical resection remains the only curative treatment. These tumors can recur even after optimal surgery, classified R0, i.e. without microscopic residue (in about 10% of cases). Different pathological prognostic factors are known, including initial tumor size, FNCLCC histological grade scheme and deep tumor location. At present, there is no available marker to predict the risk of recurrence following curative surgical resection of a sarcoma, which complicates the clinical decision making.So far, studies have focused on the features of tumor cells but the features of tissue margins surrounding sarcoma cells are unknown. The margin constitutes the interface between the tumor tissue and the healthy tissue, it is a remodeled tissue located in direct contact with the tumor cells. The mode of tumor cell infiltration differs from one tumor to another and could modulate or reflect the risk of local relapse. Interestingly, a molecular signature predictive of local relapse has been identified in hepatocellular carcinoma by studying of the “healthy tissue”, but no data is available in sarcomas. This thesis project aims at identifying predictive factors of local tumor relapse by systematically and comparatively studying the tumor and its peripheral zones, including the central tumor zone (Tc), peripheral tumor zone (Tp), healthy peritumoral tissue in contact tumor cells (HT-R1) and remote healthy tissue (HT) in a retrospective series of 144 soft tissue sarcomas.In a first part, we have characterized the immune infiltrate associated with sarcomas by systematically studying the tissue margin with a focus on tertiary lymphoid structures (TLS), a predictive factor of response to immunotherapy in sarcomas using microscopy and immunohistochemistry. The distribution of TLS predominates in the tumor margin and seems to be correlated with a better prognosis.The second part studied by deep learning (DL) the different tumor areas using scanned slides to highlight new unknown predictive morphological factors correlated with relapse and to establish a predictive Deep learning (DL) signature of local relapse. The DL score exceeds the survival curves associated with the FNCLCC grade; the current gold standard used to assess patient risk in clinical practice.A third approach compared the transcriptome of the different tumor areas determined by whole RNA-sequencing to identify deregulated biomarkers in the different areas and to determine the immunological signatures in the different territories. Genes of interest have been highlighted in the marginal zone that may be associated with the risk of relapse. Finally, a spatial transcriptomic analysis by Visium technique was carried out on a few cases on an exploratory basis.Our study has evidenced biomarkers correlated with a higher risk of relapse that could allow in the future to identify high risk patients to personalize their follow-up and validate complementary therapeutic modalities

碩士
國立陽明大學
腦科學研究所
107
Diffusion magnetic resonance imaging (dMRI) is a technique for the non-invasive characterization of the microstructure in biological tissues since it is sensitive for the diffusion processes of hydrogen molecules. dMRI is a promising candidate for in vivo quantification of neurite morphology in white matter. Over the past two decades, conventional dMRI method usually focused on Diffusion Tensor Imaging (DTI). DTI was widely used to assess the organization of tissue in white matter, providing some indices to describe changes in biology. The model of DTI describes the diffusive water molecules relevant to free diffusion or hindered anisotropic diffusion homogeneous within each voxel based on the assumption of Gaussian distribution. However, DTI was obtained at single b-value and lacked of specificity for describing tissues in this assumption. Additionally, several advanced dMRI techniques, especially multi-compartment models, have been proposed with complicated assumption for estimating neuron morphology. Neurite Orientation Dispersion and Density Imaging (NODDI) is a clinically feasible technique for estimating the microstructural complexity in central neuron system imaging, post by Zhang et al. in 2012. NODDI is a multi-compartment tissue model based on dMRI, combining a three-compartment tissue model: restricted compartment for non-Gaussian anisotropic diffusion (referring to the space bounded by the membrane of neurites), hindered compartment for Gaussian anisotropic diffusion (referring to the space around the neurites) and isotropic compartment for Gaussian diffusion (referring to the CSF space) in each voxel. Using three compartments, NODDI map not only axons in the white matter but also dendrites in gray matter in each voxel. Compared to DTI indices, NODDI may provide greater specificity to morphology and pathology, e.g. neurite density and orientation dispersion. The aims of this work are to explore the promising indices of diffusion models in characterizing the microstructural complexity in the peritumoral area of gliomas and to show the clinical feasibility and potential capability of NODDI studies. The first chapter gave an overview of dMRI and explained the models of NODDI as well as DTI (Chapter 1). In the chapters 2~5, we investigated the different preprocessing interference on NODDI and DTI as verified by topography of corpus callosum for optimization (Chapter 2), and then we differentiated different types of gliomas and characterized the infiltration in peritumoral area by NODDI and DTI using the optimized preprocessing method (Chapter 3); furthermore, we in-vivo evaluated the simplified NODDI imaging protocol and constructed the semi-automatic regions of interest (ROI) delineation for peritumoral areas (Chapter 4 and 5). Finally, the last chapter gave a conclusion of this thesis (Chapter 6).

Hemangioblastomas are benign central nervous system tumors that are found primarily (99%) in the cerebellum, brainstem, and spinal cord. They can occur sporadically (67% of cases) or in the context of the familial neoplasia syndrome, von Hippel-Lindau disease (VHL; 33%). These lesions often remain quiescent or grow in a saltatory pattern. When these tumors cause signs or symptoms, the signs or symptoms are often associated with peritumoral cyst formation. Whether the tumor occurs sporadically or in the context of VHL, complete resection is the treatment of choice when necessary. This chapter describes the clinical, imaging, and treatment features of this neoplasm.

Malignant brain tumors are devastating, and increased survival requires new therapeutic modalities. Metabolic dysregulation results in an increased need for glucose in tumor cells, suggesting that reduced tumor growth could be achieved with decreased glucose availability either through pharmacological means or use of a high-fat, low-carbohydrate ketogenic diet (KD). KD provides increased blood ketones to support energy needs of normal tissues and has been shown to reduce tumor growth, angiogenesis, inflammation, peritumoral edema, migration, and invasion. Furthermore, this diet can enhance the activity of radiation and chemotherapy in a mouse model of glioma, thus increasing survival. In vitro studies indicate that increasing ketones in the absence of glucose reduction can also inhibit cell growth and potentiate the effects of radiation. Thus, emerging data provide strong support for the use of KD in the treatment of malignant gliomas and thus far has led to a limited number of clinical trials.

Long-term epilepsy-associated tumours (LEATs) are usually dysembryoplastic neuroepithelial tumours (DNTs) and gangliogliomas. Both usually show childhood-onset intractable partial epilepsy, concordant focal EEG abnormalities, and predominant temporal location. Imaging showing typical pseudocystic pattern is suggestive of DNT. Gangliogliomas are characterized by association of a true cyst and nodular contrast enhancement. However, less typical patterns may also be seen, rendering differentiation between the two difficult. Stereo-EEG has demonstrated intrinsic epileptogenicity of both, the typical interictal pattern consisting of repetitive spikes on depressed background activity. Ictal onset discharges arise from tumour in all cases, spreading to peritumoural and secondarily distant areas. Intratumoural stimulations elicit seizures similar to spontaneous seizures. Hippocampus is involved early in most temporal tumours. Epileptogenic zone organization differs according to DNT subtypes, co-localized with tumour in simple and complex forms, and more extended in non-specific forms. In gangliogliomas, the epileptogenic zone is similar to that observed in non-specific DNTs.

Corticosteroids have been in use for decades and are one of the most prescribed drugs in all specialties of medicine. Jerome Posner, in his classic textbook “Neurological Complications of Cancer,” refers to corticosteroids as widely used drugs in neuro-oncology leading to a remarkable decline in perioperative mortality and morbidity rates. Being the most powerful class of tumor-induced-edema reducing agents, they are adjuvant to chemotherapy and are also known to reduce the risk of encephalopathy and other associated neurological deficits in patients undergoing radiation therapy. They have been widely used in higher-than-normal doses in the management of pathologic, immunological, and inflammatory conditions and various other diseases. Novel insights into the mechanisms of action of corticosteroids and their effects on cancer patients are extensively being studied. While substantial clinical improvements can be seen in cancer patients, corticosteroids are also associated with adverse and well-characterized side effects leading to immediate as well as long-term complications in patients. This chapter reviews the clinical aspects of corticosteroid therapy used in neuro-oncological conditions and its effects on peritumoral edema. Although there is currently insufficient information on appropriate use, in most cases, corticosteroids are used in a supraphysiological and pharmacological manner to minimize the symptoms of cerebral edema. Due to limited clinical studies and evident side effects presenting synonymously with corticosteroid therapy, the emerging role of steroid-sparing drugs such as corticotrophin-releasing factors, tyrosine kinase inhibitors, and VEGF inhibitors will also be discussed.

Malignant brain tumors are devastating despite aggressive treatments, including surgical resection, chemotherapy, and radiation therapy. The average life expectancy of patients with newly diagnosed glioblastoma is approximately 18 months, and increased survival requires the design of new therapeutic modalities, especially those that enhance currently available treatments. One novel therapeutic arena is the metabolic dysregulation that results in an increased need for glucose in tumor cells. This phenomenon suggests that a reduction in tumor growth could be achieved by decreasing glucose availability, which can be accomplished through pharmacologic means or through the use of a high-fat, low-carbohydrate ketogenic diet (KD). Preclinical work has shown that the KD does indeed reduce tumor growth in vivo, and it reduces angiogenesis, inflammation, peritumoral edema, migration, and invasion. Furthermore, the KD can enhance the activity of radiation and chemotherapy in a mouse model of glioma, thus increasing survival. Additional studies in vitro have indicated that increasing ketones in the absence of glucose reduction can also inhibit cell growth and potentiate the effects of radiation. The pluripotent effects exhibited by ketogenic therapy may be due, in part, to epigenetic changes. The main ketone, β‎-hydroxybutyrate, is a class 1 histone deacetylase inhibitor, and we have shown that the expression of a number of microRNAs is altered in tumors of mice fed a KD compared to standard diet. Thus, the emerging data provide strong support for the use of a KD in the treatment of malignant gliomas.

Introduction: The broad acceptance of sentinel lymph node biopsy (SLNB) led to an analysis for finding out the anatomopathological characteristics that can help predict the involvement of other axillary lymph nodes (LN) in positive sentinel lymph node (SLN) cases. Currently, it is very appropriate to investigate the cases that enable the omission of complete axillary dissection (CAD), even considering the involvement of the SLN. Some important studies on this theme were published, e.g., ACOSOG Z0011, and AMAROS. However, their results were not accepted uniformly enough because of methodological inconsistencies. Objectives: We aimed at providing a complementary basis for a pragmatic analysis of CAD after a positive SLNB in breast cancer. Methods: This is a cross-sectional study. Clinical and anatomopathological data were collected in patients with early-infiltrating breast cancer that were treated with SLNB, followed by CAD. Statistical analyses were performed using binary logistic regression and multiple logistic regression. Results: Out of 129 patients evaluated, compromise of non-sentinel additional lymph nodes was observed in 47 (36.4%) patients. According to an univariate analysis, the parameters related to non-SLN compromise were the tumor size in anatomopathological exam, histological grade III, the presence of peritumoral vascular embolism in focal area, compromise of more than one SLN, LN compromise rate of 100%, the presence of extracapsular neoplastic extension, perilymphnodal vascular involvement, perilymphatic fat compromise, and twenty or more dissected non-SNLs. The variables that increased the chance of compromise of non-SNL in the multivariate analysis were presented in following table with an accuracy of 81% (Figure). Conclusions: The tumor size on a clinical examination of the T2 category, the presence of two or more neoplastic foci in the SNL, and the size of the metastasis > 4.0 mm are the parameters that favor complete axillary lymphadenectomy.

Introduction: Since 2013, after the Saint Gallen International Breast Cancer Conference, breast cancer is classified by its morphological, biological and prognostic features into three subgroups according to the immunohistochemichal expression, which is similar to the genetic expression of the tumor. These groups, known as luminal, HER2 enriched and triple negative, are classified according to the positivity or negativity of nuclear receptors (estrogen [ER] and progesterone receptors [PR]) or membrane receptors (HER2). Triple negative tumors do not express positivity for any of these receptors. This group is composed of tumors with a more adverse biology and more aggressive behavior, affecting women in a younger age than other groups, and they also have higher rates of recurrence and lower overall survival. Objectives: This study aims to assess morphological and angiogenic features of these tumors by ultrasound exams. Methods: This is a prospective study, in which 129 lesions with an immunochemistry study compatible with triple negative tumors were selected from 1,180 breast carcinomas diagnosed by ultrasound and core biopsy from 2012 to 2017. Features assessed were shape, margin, posterior acoustic effect, reaction of the surrounding tissue, presence of calcifications within the lesion, presence of vascular flow with resistance index (RI), pulsatility index (PI), and maximum velocity of the vascular flow (Vmax). Results: Among the 129 tumors included, oval shape was the most prevalent with 72 cases (56%), 43 tumors (33%) had an irregular shape, and only 14 (11%) were round. As for their margin, the most prevalent was microlobulated, observed in 60 cases (46%), followed by circumscribed (35 cases, 27%), indistinct (19 cases, 15%), and the less frequent margins were angled and spiculated, with 10 (8%) and 5 cases (4%), respectively. The most prevalent posterior acoustic effect was enhancement (50 cases, 39%), followed by absence of posterior effect (38 cases, 27%), mixed effect (23 cases, 18%) and the least frequent was acoustic shadowing, accounting for only 18 cases (14%). The absolute majority of the tumors, 92% lesions in total, did not present calcifications within the lesion and 89% did not have a hyperechogenic halo in the surrounding tissue, presenting with abrupt lesion limits. From all cases, 110 (85%) had normal peritumoral tissue, causing no tissue thickening. In relation to the angiogenic study, most lesions had vascular flow (81 cases, 63%). The mean PI was 1.5, RI was 0.7 and the average Vmax was 19.7 cm/s. Conclusions: From an ultrasonographic point of view, some prevalent feautres are noted, which can help in their radiogenomic determination. Oval shape, abrupt interface, microlobulated margins, posterior acoustic enhancement, absence of internal microcalcifications and hyperechogenic halo prevailed.