Study of the role of particle-particle dipole interaction in dielectrophoretic devices for biomarkers identification

A three dimensional Coupled Monte Carlo-Poisson method has been used to evaluate the impact of particle-particle dipole interactions in the equilibrium distribution of a system of uncharged polarizable particles suspended in a static liquid medium under the action of an oscillating non-uniform electric field generated by polynomial electrodes. We compare the simulated distributions with experimental ones both for micro- (MDA-MB-231 breast tumor cells) and nano-(multiwall carbon nanotubes) particles. In both cases the equilibrium distributions near the electrodes are dominated by dipole interactions which locally enhance the DEP effect and promote long particles chains.

A fully automatic approach for multimodal PET and MR image segmentation in gamma knife treatment planning

The aim of this study is to combine Biological Target Volume (BTV) segmentation and Gross Target Volume (GTV) segmentation in stereotactic neurosurgery.Our goal is to enhance Clinical Target Volume (CTV) definition, including metabolic and morphologic information, for treatment planning and patient follow-up.We propose a fully automatic approach for multimodal PET and MR image segmentation. This method is based on the Random Walker (RW) and Fuzzy C-Means clustering (FCM) algorithms. A total of 19 brain metastatic tumors, undergone stereotactic neuro-radiosurgery, were retrospectively analyzed. A framework for the evaluation of multimodal PET/MRI segmentation is presented, considering volume…

Theoretical and experimental study of the role of cell-cell dipole interaction in dielectrophoretic devices: application to polynomial electrodes

BACKGROUND: We aimed to investigate the effect of cell-cell dipole interactions in the equilibrium distributions in dielectrophoretic devices. METHODS: We used a three dimensional coupled Monte Carlo-Poisson method to theoretically study the final distribution of a system of uncharged polarizable particles suspended in a static liquid medium under the action of an oscillating non-uniform electric field generated by polynomial electrodes. The simulated distributions have been compared with experimental ones observed in the case of MDA-MB-231 cells in the same operating conditions. RESULTS: The real and simulated distributions are consistent. In both cases the cells distribution near the elec…

79. Amyloid-PET analysis based on tissue probability maps

Purpose The regional quantification of amyloid burden is crucial for the clinical diagnosis of Alzheimer’s disease [1]. The best method to evaluate regional amyloid deposition in PET is through the use MR imaging for brain space normalization. However, since MR imaging is not always available in the clinical practice, a MR-less methodology is needed in order to compute semi-quantitative and analyze regional amyloid burden. Methods Forty-four patients with clinical evidence of dementia, underwent 18F-Florbetaben PET (FBB-PET), FDG-PET, neuropsychological assessment and cerebrospinal fluid analysis. We implemented a methodology that uses SPM12 to import and normalize the FBB-PET images in Mon…

Cytokine profile of breast cell lines after different radiation doses

Purpose: Ionizing radiation (IR) treatment activates inflammatory processes causing the release of a great amount of molecules able to affect the cell survival. The aim of this study was to analyze the cytokine signature of conditioned medium produced by non-tumorigenic mammary epithelial cell line MCF10A, as well as MCF7 and MDA-MB-231 breast cancer cell lines, after single high doses of IR in order to understand their role in high radiation response. Materials and methods: We performed a cytokine profile of irradiated conditioned media of MCF10A, MCF7 and MDA-MB-231 cell lines treated with 9 or 23 Gy, by Luminex and ELISA analyses. Results: Overall, our results show that both 9 Gy and 23 …

Computer-Assisted Approaches for Uterine Fibroid Segmentation in MRgFUS Treatments: Quantitative Evaluation and Clinical Feasibility Analysis

Nowadays, uterine fibroids can be treated using Magnetic Resonance guided Focused Ultrasound Surgery (MRgFUS), which is a non-invasive therapy exploiting thermal ablation. In order to measure the Non-Perfused Volume (NPV) for treatment response assessment, the ablated fibroid areas (i.e., Region of Treatment, ROT) are manually contoured by a radiologist. The current operator-dependent methodology could affect the subsequent follow-up phases, due to the lack of result repeatability. In addition, this fully manual procedure is time-consuming, considerably increasing execution times. These critical issues can be addressed only by means of accurate and efficient automated Pattern Recognition ap…

Combining split-and-merge and multi-seed region growing algorithms for uterine fibroid segmentation in MRgFUS treatments

Uterine fibroids are benign tumors that can affect female patients during reproductive years. Magnetic resonance-guided focused ultrasound (MRgFUS) represents a noninvasive approach that uses thermal ablation principles to treat symptomatic fibroids. During traditional treatment planning, uterus, fibroids, and surrounding organs at risk must be manually marked on MR images by an operator. After treatment, an operator must segment, again manually, treated areas to evaluate the non-perfused volume (NPV) inside the fibroids. Both pre- and post-treatment procedures are time-consuming and operator-dependent. This paper presents a novel method, based on an advanced direct region detection model, …

Biological target volume segmentation for radiotherapy treatment planning

Clinical support in radiation therapy scenarios: MR brain tumor segmentation using an unsupervised fuzzy C-Means clustering technique

Gene expression profiles in irradiated cancer cells

Knowledge of the molecular and genetic mechanisms underlying cellular response to radiation may provide new avenues to develop innovative predictive tests of radiosensitivity of tumours and normal tissues and to improve individual therapy. Nowadays very few studies describe molecular changes induced by hadrontherapy treatments, therefore this field has to be explored and clarified. High-throughput methodologies, such as DNA microarray, allow us to analyse mRNA expression of thousands of genes simultaneously in order to discover new genes and pathways as targets of response to hadrontherapy. Our aim is to elucidate the molecular networks involved in the sensitivity/resistance of cancer cell …

Gamma Knife treatment planning: MR brain tumor segmentation and volume measurement based on unsupervised Fuzzy C-Means clustering

Nowadays, radiation treatment is beginning to intensively use MRI thanks to its greater ability to discriminate healthy and diseased soft-tissues. Leksell Gamma Knife® is a radio-surgical device, used to treat different brain lesions, which are often inaccessible for conventional surgery, such as benign or malignant tumors. Currently, the target to be treated with radiation therapy is contoured with slice-by-slice manual segmentation on MR datasets. This approach makes the segmentation procedure time consuming and operator-dependent. The repeatability of the tumor boundary delineation may be ensured only by using automatic or semiautomatic methods, supporting clinicians in the treatment pla…

USE-Net: Incorporating Squeeze-and-Excitation blocks into U-Net for prostate zonal segmentation of multi-institutional MRI datasets

Prostate cancer is the most common malignant tumors in men but prostate Magnetic Resonance Imaging (MRI) analysis remains challenging. Besides whole prostate gland segmentation, the capability to differentiate between the blurry boundary of the Central Gland (CG) and Peripheral Zone (PZ) can lead to differential diagnosis, since tumor's frequency and severity differ in these regions. To tackle the prostate zonal segmentation task, we propose a novel Convolutional Neural Network (CNN), called USE-Net, which incorporates Squeeze-and-Excitation (SE) blocks into U-Net. Especially, the SE blocks are added after every Encoder (Enc USE-Net) or Encoder-Decoder block (Enc-Dec USE-Net). This study ev…

Neuro-radiosurgery treatments: MRI brain tumor seeded image segmentation based on a cellular automata model

Gross Tumor Volume (GTV) segmentation on medical images is an open issue in neuro-radiosurgery. Magnetic Resonance Imaging (MRI) is the most promi-nent modality in radiation therapy for soft-tissue anatomical districts. Gamma Knife stereotactic neuro-radiosurgery is a mini-invasive technique used to deal with inaccessible or insufficiently treated tumors. During the planning phase, the GTV is usually contoured by radiation oncologists using a manual segmentation procedure on MR images. This methodology is certainly time-consuming and op-erator-dependent. Delineation result repeatability, in terms of both intra- and inter-operator reliability, is only obtained by using computer-assisted appr…

Using anatomic and metabolic imaging in stereotactic radio neuro-surgery treatments

Automated prostate gland segmentation based on an unsupervised fuzzy C-means clustering technique using multispectral T1w and T2w MR imaging

Prostate imaging analysis is difficult in diagnosis, therapy, and staging of prostate cancer. In clinical practice, Magnetic Resonance Imaging (MRI) is increasingly used thanks to its morphologic and functional capabilities. However, manual detection and delineation of prostate gland on multispectral MRI data is currently a time-expensive and operator-dependent procedure. Efficient computer-assisted segmentation approaches are not yet able to address these issues, but rather have the potential to do so. In this paper, a novel automatic prostate MR image segmentation method based on the Fuzzy C-Means (FCM) clustering algorithm, which enables multispectral T1-weighted (T1w) and T2-weighted (T…

A Survey on Nature-Inspired Medical Image Analysis: A Step Further in Biomedical Data Integration

Natural phenomena and mechanisms have always intrigued humans, inspiring the design of effective solutions for real-world problems. Indeed, fascinating processes occur in nature, giving rise to an ever-increasing scientific interest. In everyday life, the amount of heterogeneous biomedical data is increasing more and more thanks to the advances in image acquisition modalities and high-throughput technologies. The automated analysis of these large-scale datasets creates new compelling challenges for data-driven and model-based computational methods. The application of intelligent algorithms, which mimic natural phenomena, is emerging as an effective paradigm for tackling complex problems, by…

CNN-Based Prostate Zonal Segmentation on T2-Weighted MR Images: A Cross-Dataset Study

Prostate cancer is the most common cancer among US men. However, prostate imaging is still challenging despite the advances in multi-parametric magnetic resonance imaging (MRI), which provides both morphologic and functional information pertaining to the pathological regions. Along with whole prostate gland segmentation, distinguishing between the central gland (CG) and peripheral zone (PZ) can guide toward differential diagnosis, since the frequency and severity of tumors differ in these regions; however, their boundary is often weak and fuzzy. This work presents a preliminary study on deep learning to automatically delineate the CG and PZ, aiming at evaluating the generalization ability o…

CNN-based Prostate Zonal Segmentation on T2-weighted MR Images: A Cross-dataset Study

Prostate cancer is the most common cancer among US men. However, prostate imaging is still challenging despite the advances in multi-parametric Magnetic Resonance Imaging (MRI), which provides both morphologic and functional information pertaining to the pathological regions. Along with whole prostate gland segmentation, distinguishing between the Central Gland (CG) and Peripheral Zone (PZ) can guide towards differential diagnosis, since the frequency and severity of tumors differ in these regions; however, their boundary is often weak and fuzzy. This work presents a preliminary study on Deep Learning to automatically delineate the CG and PZ, aiming at evaluating the generalization ability …

Metabolic Response Assessment in Non-Small Cell Lung Cancer Patients after Platinum-Based Therapy: A Preliminary Analysis

The purpose of this study was to evaluate the clinical value of PET (Positron Emission Tomography) for early prediction of tumor response to platinum-based therapy in patients with nonsmall cell lung cancer (NSCLC). The evaluation was carried out comparing the standard treatment response using RECIST (Response Evaluation Criteria in Solid Tumors) with metabolic treatment response according to European Organization for Research and Treatment of Cancer (EORTC) recommendations, PET Response Criteria in Solid Tumors (PERCIST), Total Lesion Glycolysis (TLG) and Metabolic Tumor Volume (MTV). Seventeen inoperable patients with stage IV NSCLC were enrolled between October 2011 and June 2013: PET st…

A fully automatic method for biological target volume segmentation of brain metastases

Leksell Gamma Knife is a mini-invasive technique to obtain a complete destruction of cerebral lesions delivering a single high dose radiation beam. Positron Emission Tomography (PET) imaging is increasingly utilized for radiation treatment planning. Nevertheless, lesion volume delineation in PET datasets is challenging because of the low spatial resolution and high noise level of PET images. Nowadays, the biological target volume (BTV) is manually contoured on PET studies. This procedure is time expensive and operator-dependent. In this article, a fully automatic algorithm for the BTV delineation based on random walks (RW) on graphs is proposed. The results are compared with the outcomes of…

A Graph-Based Method for PET Image Segmentation in Radiotherapy Planning: A Pilot Study

Target volume delineation of Positron Emission Tomography (PET) images in radiation treatment planning is challenging because of the low spatial resolution and high noise level in PET data. The aim of this work is the devel- opment of an accurate and fast method for semi-automatic segmentation of me- tabolic regions on PET images. For this purpose, an algorithm for the biological tumor volume delineation based on random walks on graphs has been used. Va- lidation was first performed on phantoms containing spheres and irregular in- serts of different and known volumes, then tumors from a patient with head and neck cancer were segmented to discuss the clinical applicability of this algo- rith…

Portrait of inflammatory response to ionizing radiation treatment

Ionizing radiation (IR) activates both pro-and anti-proliferative signal pathways producing an imbalance in cell fate decision. IR is able to regulate several genes and factors involved in cell-cycle progression, survival and/or cell death, DNA repair and inflammation modulating an intracellular radiation-dependent response. Radiation therapy can modulate anti-tumour immune responses, modifying tumour and its microenvironment. In this review, we report how IR could stimulate inflammatory factors to affect cell fate via multiple pathways, describing their roles on gene expression regulation, fibrosis and invasive processes. Understanding the complex relationship between IR, inflammation and …

An automatic method for metabolic evaluation of gamma knife treatments

Lesion volume delineation of Positron Emission Tomography images is challenging because of the low spatial resolution and high noise level. Aim of this work is the development of an operator independent segmentation method of metabolic images. For this purpose, an algorithm for the biological tumor volume delineation based on random walks on graphs has been used. Twenty-four cerebral tumors are segmented to evaluate the functional follow-up after Gamma Knife radiotherapy treatment. Experimental results show that the segmentation algorithm is accurate and has real-time performance. In addition, it can reflect metabolic changes useful to evaluate radiotherapy response in treated patients.

A fully automatic 2D segmentation method for uterine fibroid in MRgFUS treatment evaluation

PurposeMagnetic Resonance guided Focused UltraSound (MRgFUS) represents a non-invasive surgical approach that uses thermal ablation to treat uterine fibroids. After the MRgFUS treatment, an operator must manually segment the treated fibroid areas to evaluate the NonPerfused Volume (NPV). This manual approach is operator-dependent, introducing issues of result reproducibility, which could lead to errors in the subsequent follow-up phase. Moreover, manual segmentation is time-consuming, and can have a negative impact on the optimization of both machine-time and operator-time. MethodTo address these issues, in this paper a novel fully automatic method based on the unsupervised Fuzzy C-Means cl…

Semi-automatic Brain Lesion Segmentation in Gamma Knife Treatments Using an Unsupervised Fuzzy C-Means Clustering Technique

MR Imaging is being increasingly used in radiation treatment planning as well as for staging and assessing tumor response. Leksell Gamma Knife (R) is a device for stereotactic neuro-radiosurgery to deal with inaccessible or insufficiently treated lesions with traditional surgery or radiotherapy. The target to be treated with radiation beams is currently contoured through slice-by-slice manual segmentation on MR images. This procedure is time consuming and operator-dependent. Segmentation result repeatability may be ensured only by using automatic/semi-automatic methods with the clinicians supporting the planning phase. In this paper a semi-automatic segmentation method, based on an unsuperv…

253. An accurate and operator independent method for biological tumour volume segmentation

Purpose The aim of this paper is to develop an operator independent method for biological tumour volume (BTV) delineation from Positron Emission Tomography (PET) images. BTV delineation is challenging because of the low spatial resolution and high noise level in PET images. In addition, BTV varies substantially depending on the method used to segment. Manual delineation is widely-used, but it is strongly user dependent. Methods The proposed method starts with the automatic identification of the PET slice with maximum Standardized Uptake Value (SUV). Then, a user- independent mask is obtained by a rough pre-segmentation step and it is used to perform the local active contour segmentation on …

A Semi-automatic Multi-seed Region-Growing Approach for Uterine Fibroids Segmentation in MRgFUS Treatment

Fibroids are benign tumors growing in the uterus. Most of fibroids do not require treatment unless they are causing symptoms. Traditional surgery treatments, like myomectomy and hysterectomy, are very invasive therapeutic approaches which not always preserves reproductive potential of the woman. MRgFUS, performed with Insightec ExAblate 2100 equipment, is a new and noninvasive technique for uterine fibroids treatment, not requiring hospitalization and recovery time for patients. An initial assessment of MRgFUS treatment is made by computing the ablated volume of uterine fibroid. In this paper a semi-automatic approach, based on region-growing segmentation technique, is proposed. The impleme…

Fully automatic multispectral MR image segmentation of prostate gland based on the fuzzy C-means clustering algorithm

Prostate imaging is a very critical issue in the clinical practice, especially for diagnosis, therapy, and staging of prostate cancer. Magnetic Resonance Imaging (MRI) can provide both morphologic and complementary functional information of tumor region. Manual detection and segmentation of prostate gland and carcinoma on multispectral MRI data is not easily practicable in the clinical routine because of the long times required by experienced radiologists to analyze several types of imaging data. In this paper, a fully automatic image segmentation method, exploiting an unsupervised Fuzzy C-Means (FCM) clustering technique for multispectral T1-weighted and T2-weighted MRI data processing, is…

Genotyping analysis and 18FDG uptake in breast cancer patients: a preliminary research

Background: Diagnostic imaging plays a relevant role in the care of patients with breast cancer (BC). Positron Emission Tomography (PET) with 18F-fluoro-2-deoxy-D-glucose (FDG) has been widely proven to be a clinical tool suitable for BC detection and staging in which the glucose analog supplies metabolic information about the tumor. A limited number of studies, sometimes controversial, describe possible associations between FDG uptake and single nucleotide polymorphisms (SNPs). For this reason this field has to be explored and clarified. We investigated the association of SNPs in GLUT1, HIF-1a, EPAS1, APEX1, VEGFA and MTHFR genes with the FDG uptake in BC. Methods: In 26 caucasian individu…

NeXt for neuro-radiosurgery: A fully automatic approach for necrosis extraction in brain tumor MRI using an unsupervised machine learning technique

Stereotactic neuro-radiosurgery is a well-established therapy for intracranial diseases, especially brain metastases and highly invasive cancers that are difficult to treat with conventional surgery or radiotherapy. Nowadays, magnetic resonance imaging (MRI) is the most used modality in radiation therapy for soft-tissue anatomical districts, allowing for an accurate gross tumor volume (GTV) segmentation. Investigating also necrotic material within the whole tumor has significant clinical value in treatment planning and cancer progression assessment. These pathological necrotic regions are generally characterized by hypoxia, which is implicated in several aspects of tumor development and gro…

Metabolic impact of Partial Volume Correction of [18F]FDG PET-CT oncological studies on the assessment of tumor response to treatment

AIM: The aim of this work is to evaluate the metabolic impact of Partial Volume Correction (PVC) on the measurement of the Standard Uptake Value (SUV) from [18F]FDG PET-CT oncological studies for treatment monitoring purpose. METHODS: Twenty-nine breast cancer patients with bone lesions (42 lesions in total) underwent [18F]FDG PET-CT studies after surgical resection of breast cancer primitives, and before (PET-I) and after (PET-II) chemotherapy and hormone treatment. PVC of bone lesion uptake was performed on the two [18F]FDG PET-CT studies, using a method based on Recovery Coefficients (RC) and on an automatic measurement of lesion metabolic volume. Body-weight average SUV was calculated f…

Genetic, clinical and radiographic signs in knee osteoarthritis susceptibility

Abstract INTRODUCTION: Osteoarthritis (OA) is considered to be a multifactorial and polygenic disease and diagnosis is mainly clinical and radiological. Correlation between radiographic data and clinical status has been reported. However, very few studies, especially in Caucasian people, describe the association between the Kellgren and Lawrence OA grading scale (KL) and genetic alterations to better understand OA etiopathogenesis and susceptibility. In order to update the knee OA grading, in this study we assessed the associations between KL grade, clinical features such as American Knee Society Score (AKSS), age, and polymorphisms in the principal osteoarthritis susceptibility (OS) genes …