1,721,003 research outputs found
Motion Management in Positron Emission Tomography/Computed Tomography for Radiation Treatment Planning
No full textHybrid positron emission tomography (PET)/computed tomography (CT) scanners combine, in a unique gantry, 2 of the most important diagnostic imaging systems, a CT and a PET tomograph, enabling anatomical (CT) and functional (PET) studies to be performed in a single study session. Furthermore, as the 2 scanners use the same spatial coordinate system, the reconstructed CT and PET images are spatially co-registered, allowing an accurate localization of the functional signal over the corresponding anatomical structure. This peculiarity of the hybrid PET/CT system results in improved tumor characterization for oncological applications, and more recently, it was found to be also useful for target volume definition (TVD) and treatment planning in radiotherapy (RT) applications. In fact, the use of combined PET/CT information has been shown to improve the RT treatment plan when compared with that obtained by a CT alone. A limiting factor to the accuracy of TVD by PET/CT is organ and tumor motion, which is mainly due to patient respiration. In fact, respiratory motion has a degrading effect on PET/CT image quality, and this is also critical for TVD, as it can lead to possible tumor missing or undertreatment. Thus, the management of respiratory motion is becoming an increasingly essential component in AT treatment planning; indeed, it has been recognized that the use of personalized motion information can improve TVD and, consequently, permit increased tumor dosage while sparing surrounding healthy tissues and organs at risk. This review describes the methods used for motion management in PET/CT for radiation treatment planning. The article covers the following: (1) problems caused by organ and lesion motion owing to respiration, and the artifacts generated on CT, PET, and PET/CT images; (2) data acquisition and processing techniques used to manage respiratory motion in PET/CT studies; and (3) the use of personalized motion information for TVD and radiation treatment planning. Semin Nucl Med 42:289-307 (c) 2012 Elsevier Inc. All rights reserved
Combining split-and-merge and multi-seed region growing algorithms for uterine fibroid segmentation in MRgFUS treatments
No full textUterine 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, for fibroid segmentation in MR images to address MRgFUS post-treatment segmentation issues. An incremental procedure is proposed: split-and-merge algorithm results are employed as multiple seed-region selections by an adaptive region growing procedure. The proposed approach segments multiple fibroids with different pixel intensity, even in the same MR image. The method was evaluated using area-based and distance-based metrics and was compared with other similar works in the literature. Segmentation results, performed on 14 patients, demonstrated the effectiveness of the proposed approach showing a sensitivity of 84.05 %, a specificity of 92.84 %, and a speedup factor of 1.56× with respect to classic region growing implementations (average values)
Gene Expression Profiling of Epithelial–Mesenchymal Transition in Primary Breast Cancer Cell Culture
No full textBackground/Aim: Epithelial–mesenchymal transition
(EMT) is a process co-opted by cancer cells to invade and form
metastases. In the present study we analyzed gene expression
profiles of primary breast cancer cells in culture in order to
highlight genes related to EMT. Materials and Methods:
Microarray expression analysis of primary cells isolated from
a specimen of a patient with an infiltrating ductal carcinoma of
the breast was performed. Real-Time Quantitative Reverse
Transcription PCR (qRT-PCR) analyses validated microarray
gene expression trends. Results: Thirty-six candidate genes were
selected and used to generate a molecular network displaying
the tight relationship among them. The most significant Gene
Ontology biological processes characterizing this network were
involved in cell migration and motility. Conclusion: Our data
revealed the involvement of new genes which displayed tight
relationships among them, suggesting a molecular network in
which they could contribute to control of EMT in breast cancer.
This study may offer a basis for understanding complex
mechanisms which regulate breast cancer progression and for
designing individualized anticancer therapies
A fully automatic 2D segmentation method for uterine fibroid in MRgFUS treatment evaluation
No full textPurpose: Magnetic 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. Method: To address these issues, in this paper a novel fully automatic method based on the unsupervised Fuzzy C-Means clustering and iterative optimal threshold selection algorithms for uterus and fibroid segmentation is proposed. The developed method could be used to enhance the current manual methodology performed by healthcare operators for post-operative NPV evaluation in uterine fibroid MRgFUS treatments. Results: The proposed method was tested on 15 MR datasets of 15 different patients with uterine fibroids and evaluated using area-based and distance-based metrics. A comparison of extracted volume was also performed. Average values for fibroid (ROT) segmentation are SDI=88.67%, JI=80.70%, SE=89.79%, SP=88.73%, MAD=2.200 [pixels], MAXD=6.233 [pixels] and HD=2.988 [pixels]. Moreover, to make a quantitative evaluation of this method, our experimental results were compared with similar literature approaches. Conclusions: The proposed method provides a practical approach for the automatic evaluation of the boundary and volume of ablated fibroid regions, without any external user input. The achieved segmentation results show the validity and the effectiveness of the proposed solution
High Intensity Focused Ultrasound: opportunità e sfide della chirurgia ablativa non invasiva sotto guida a Risonanza Magnetica
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