Biological target volume segmentation for radiotherapy treatment planning

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…

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.

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…

Analysis of Metabolic Parameters Coming from Basal and Interim PET in Hodgkin Lymphoma

Objective: Positron Emission Tomography (PET) with F-18-Fluoro-deoxy-glucose (FDG) emerged as a prognostic tool to predict treatment outcome in Hodgkin Lymphoma (HL). Moreover, a FDG-PET adapted strategy is currently assessed in clinical trial to minimize the toxic effect while maintaining the efficacy of treatment in HL. Purpose was to analyze the quantitative parameters to support the prognostic role of FDG-PET today based on the semi-quantitative Deauville 5-point Scale (D5-PS). Methods: This retrospective study included 53 patients diagnosed with advanced-stage HL between 2009 and 2014, enrolled in the PET response-adapted clinical trial HD 0607. FDG-PET was performed at baseline (PET0)…