Early Monitoring Response to Therapy in Patients with Brain Lesions Using the Cumulative SUV Histogram

Featured Application The study proposes a methodology to evaluate the response of patients with brain lesions to Gamma Knife treatments through the use of Positron Emission Tomography imaging. Gamma Knife treatment is an alternative to traditional brain surgery and whole-brain radiation therapy for treating cancers that are inaccessible via conventional treatments. To assess the effectiveness of Gamma Knife treatments, functional imaging can play a crucial role. The aim of this study is to evaluate new prognostic indices to perform an early assessment of treatment response to therapy using positron emission tomography imaging. The parameters currently used in nuclear medicine assessments can be affected by statistical fluctuation errors and/or cannot provide information on tumor extension and heterogeneity. To overcome these limitations, the Cumulative standardized uptake value (SUV) Histogram (CSH) and Area Under the Curve (AUC) indices were evaluated to obtain additional information on treatment response. For this purpose, the absolute level of [11C]-Methionine (MET) uptake was measured and its heterogeneity distribution within lesions was evaluated by calculating the CSH and AUC indices. CSH and AUC parameters show good agreement with patient outcomes after Gamma Knife treatments. Furthermore, no relevant correlations were found between CSH and AUC indices and those usually used in the nuclear medicine environment. CSH and AUC indices could be a useful tool for assessing patient responses to therapy

MRI Characterization of Radiation Necrosis in an Animal Model: Time to Onset, Progression, and Therapeutic Response

Radiation necrosis is a severe, but late occurring type of injury to normal tissue, within and surrounding a radiation treatment field, which can lead to significant complications for neurooncology patients. Radiation necrosis is difficult to distinguish from recurrent tumor by either neurologic examination or clinical imaging protocols. Concerns for the development of radiation necrosis often limit therapeutic radiation doses. Current treatment options for radiation necrosis are limited. The development of solutions to these clinical challenges has been hampered by an appropriate animal model of radiation necrosis. With a novel mouse model of radiation necrosis developed in our lab employing a Gamma Knife, which enables high-dose, fractionated, hemispherical irradiation in the mouse brain, the objectives were to i) optimise radiation dosing schemes: total dose, fractionation) for this Gamma-Knife mouse-model of radiation necrosis; ii) determine the efficacy of bevacizumab: Avastin) and its murine analog B20-4.1.1, both vascular endothelial growth factor: VEGF) inhibitors, as mitigators of radiation necrosis in mice; iii) validate the neuroprotective effect of SB 415286, an inhibitor of glycogen synthase kinase 3β;: GSK-3β), in mouse brain following high-dose radiation treatment; and iv) identify and validate the quantitative blood oxygen level dependent: qBOLD) method as an imaging marker of radiation necrosis. For these purposes, a series of experiments were performed, including monitoring the onset and progression of radiation necrosis in mice receiving different dose schedules, comparing the development of radiation necrosis in irradiated mice with or without treatments, and mapping the irradiated and non-irradiated mouse brains using qBOLD method. It was found that i) radiation dose schedules affect the onset and progression of radiation necrosis; ii) anti-VEGF antibodies slow the progression of radiation necrosis in irradiated brain tissue; iii) SB 415286 protects against and mitigates radiation necrosis in irradiated brain tissue; and iv) a high SNR: 400 at least) is required to decouple oxygen extraction fraction: OEF) and deoxyhemoglombin cerebral blood volume: dCBV) in mouse brain using qBOLD method. In qBOLD, the voxel spread function: VSF) reduces the effect of macroscopic magnetic field inhomogeneities. However, with current shimming methods, imaging parameters, and post-processing algorithms, the resulting OEF and dCBV maps in the mouse brain are not reliable. These results demonstrated that the development of radiation necrosis in this Gamma Knife mouse model can be characterized by both anatomic MR imaging and histology. Both anti-VEGF therapy and GSK-3β inhibition could be potential therapeutic managements for radiation necrosis, but further studies are needed to optimize dosing schemes and treatment periods and elucidate mechanisms of action. Characterizing radiation necrosis in mouse brain using qBOLD remains a challenge due to the imperfect correction for macro magnetic field inhomogeneities

Trauma, Tumors, Spine, Functional Neurosurgery

This book is written for graduate students, researchers, and practitioners who are interested in learning how the knowledge from research can be implemented in clinical competences. The first section is dedicated to deep brain stimulation, a surgical procedure which is the paramount example of how clinical practice can take advantage from fundamental research. The second section gathers four chapters on four different topics and illustrates how significant is the challenge to translate scientific advances into clinical practice because the route from evidence to action is not always obvious. It is hoped that this book will stimulate the interest in the process of translating research into practice for a broader range of neurosurgical topics than the one covered by this book, which could result in a forthcoming more comprehensive publication

Development and application of rice starch based edible coating to improve the postharvest storage potential and quality of plum fruit (<i>Prunus salicina</i>)

The study investigated the possibility of enhancing the shelf life of plum fruit coated with rice starch-ι-carrageenan (RS-ι-car) composite coating blended with sucrose fatty acid esters (FAEs). Film solution (starch 3%, carrageenan 1.5% and FAEs 2%) was prepared by mixing the ingredients and properties of stand-alone films (physical, mechanical, barrier and surface morphology) were studied before applying the coating on fruit surface. Fruit were stored at 20 °C for 3 weeks and analyzed for weight loss, ethylene production, respiration rate, color change, firmness, and titratable acidity (TA) and soluble solid content (SSC). Surface morphology of stand-alone film and fruit surface (after applying on the plum fruit) was studied using scanning electron microscopy (SEM). Phytochemical analysis was performed during the storage period and total phenolic content (TPC), total antioxidant capacity (TAC), flavonoid content (FC) and free radical scavenging activity were determined. The rice starch composite coating was shown to be effective in reducing both weight loss (WL) and respiration rate and inhibiting the endogenous ethylene production when compared to the uncoated control fruit stored at room temperature (p &lt; 0.05). TPC, TAC, FC and free radical scavenging activity was unaffected in the coated fruit throughout the storage period (p &lt; 0.05). The findings reported in this study indicate that the RS-ι-car-FAEs coating prolongs the shelf life and maintains the overall quality of plum fruit during storage and could potentially be commercialized as a new edible coating for the plum fruit industry

IMAGE PROCESSING, SEGMENTATION AND MACHINE LEARNING MODELS TO CLASSIFY AND DELINEATE TUMOR VOLUMES TO SUPPORT MEDICAL DECISION

Techniques for processing and analysing images and medical data have become the main’s translational applications and researches in clinical and pre-clinical environments. The advantages of these techniques are the improvement of diagnosis accuracy and the assessment of treatment response by means of quantitative biomarkers in an efficient way. In the era of the personalized medicine, an early and efficacy prediction of therapy response in patients is still a critical issue. In radiation therapy planning, Magnetic Resonance Imaging (MRI) provides high quality detailed images and excellent soft-tissue contrast, while Computerized Tomography (CT) images provides attenuation maps and very good hard-tissue contrast. In this context, Positron Emission Tomography (PET) is a non-invasive imaging technique which has the advantage, over morphological imaging techniques, of providing functional information about the patient’s disease. In the last few years, several criteria to assess therapy response in oncological patients have been proposed, ranging from anatomical to functional assessments. Changes in tumour size are not necessarily correlated with changes in tumour viability and outcome. In addition, morphological changes resulting from therapy occur slower than functional changes. Inclusion of PET images in radiotherapy protocols is desirable because it is predictive of treatment response and provides crucial information to accurately target the oncological lesion and to escalate the radiation dose without increasing normal tissue injury. For this reason, PET may be used for improving the Planning Treatment Volume (PTV). Nevertheless, due to the nature of PET images (low spatial resolution, high noise and weak boundary), metabolic image processing is a critical task. The aim of this Ph.D thesis is to develope smart methodologies applied to the medical imaging field to analyse different kind of problematic related to medical images and data analysis, working closely to radiologist physicians. Various issues in clinical environment have been addressed and a certain amount of improvements has been produced in various fields, such as organs and tissues segmentation and classification to delineate tumors volume using meshing learning techniques to support medical decision. In particular, the following topics have been object of this study: • Technique for Crohn’s Disease Classification using Kernel Support Vector Machine Based; • Automatic Multi-Seed Detection For MR Breast Image Segmentation; • Tissue Classification in PET Oncological Studies; • KSVM-Based System for the Definition, Validation and Identification of the Incisinal Hernia Reccurence Risk Factors; • A smart and operator independent system to delineate tumours in Positron Emission Tomography scans; 3 • Active Contour Algorithm with Discriminant Analysis for Delineating Tumors in Positron Emission Tomography; • K-Nearest Neighbor driving Active Contours to Delineate Biological Tumor Volumes; • Tissue Classification to Support Local Active Delineation of Brain Tumors; • A fully automatic system of Positron Emission Tomography Study segmentation. This work has been developed in collaboration with the medical staff and colleagues at the: • Dipartimento di Biopatologia e Biotecnologie Mediche e Forensi (DIBIMED), University of Palermo • Cannizzaro Hospital of Catania • Istituto di Bioimmagini e Fisiologia Molecolare (IBFM) Centro Nazionale delle Ricerche (CNR) of Cefalù • School of Electrical and Computer Engineering at Georgia Institute of Technology The proposed contributions have produced scientific publications in indexed computer science and medical journals and conferences. They are very useful in terms of PET and MRI image segmentation and may be used daily as a Medical Decision Support Systems to enhance the current methodology performed by healthcare operators in radiotherapy treatments. The future developments of this research concern the integration of data acquired by image analysis with the managing and processing of big data coming from a wide kind of heterogeneous sources

Metabolic profile and histopathology of kidneys and liver of lambs fed silages of forages adapted to a semi-arid environment

Thirty-two mixed-breed ram lambs (average age, 5.6 ± 0.4 months, and average live weight, 17.61 ± 2.63 kg) were used to evaluate the effect of diets containing silages of forages adapted to a semi-arid environment on the metabolic profile in serum and the histopathological assessment of liver and kidney tissues of the lambs. Lambs were allocated, in a completely randomised design, to four treatments (silage of old man saltbush (Atriplex nummularia Lind), buffelgrass (Cenchrus ciliaris), gliricidia (Gliricidia sepium) and ‘pornunça’ (Manihot sp.). The feedlot period was 49 days, and animals were slaughtered at an average weight of 27 ± 4.6 kg. On the last day of the experiment, blood was collected from the jugular vein of all animals to measure the protein, metabolic and energy profiles of the lambs. At slaughter, kidney and liver samples were collected for histopathological examination. The consuming of the diet containing buffelgrass silage resulted in a significantly higher activity of alanine-aminotransferase (30.14 IU/L) and the concentrations of urea (44.25 mg/dL), creatinine (0.94 mg/dL) and albumin (4.48 g/dL) in serum. Diets containing gliricidia silage resulted in significantly higher gamma-glutamyl transferase activity (92.0 IU/L), while the diets with pornunça silage resulted in higher serum levels of triglycerides (37.85 mg/dL). The diets had no effect on aspartate-aminotransferase enzyme activity and total protein, cholesterol and globulin concentrations, or the albumin : globulin ratio in serum. Mild congestion, necrosis and foci of mineralisation were observed in the kidneys of animals fed diets containing old man saltbush (50%) and pornunça (25%) silages, and mild fatty degeneration and mild mononuclear inflammatory infiltrate in their livers. In conclusion, diets containing silages of forages that are adapted to semi-arid environments may be used for feeding lambs, given the absence of dysfunctioning plasmatic levels of liver enzymes and energy and protein profiles. Additionally, kidney failure was not observed in lambs fed these diets during the feedlot period.Keywords: blood parameters, buffelgrass, gliricidia, old man saltbush, pornunç

Image Processing and Analysis for Preclinical and Clinical Applications

Radiomics is one of the most successful branches of research in the field of image processing and analysis, as it provides valuable quantitative information for the personalized medicine. It has the potential to discover features of the disease that cannot be appreciated with the naked eye in both preclinical and clinical studies. In general, all quantitative approaches based on biomedical images, such as positron emission tomography (PET), computed tomography (CT) and magnetic resonance imaging (MRI), have a positive clinical impact in the detection of biological processes and diseases as well as in predicting response to treatment. This Special Issue, “Image Processing and Analysis for Preclinical and Clinical Applications”, addresses some gaps in this field to improve the quality of research in the clinical and preclinical environment. It consists of fourteen peer-reviewed papers covering a range of topics and applications related to biomedical image processing and analysis