ORCID Profile
0000-0003-3310-4802
Current Organisations
Paul Scherrer Institute
,
Deakin University
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Publisher: IOP Publishing
Date: 19-09-2019
Abstract: MRI-treatment units enable 2D cine-MRI centred in the tumour for motion detection in radiotherapy, but they lack 3D information due to spatio-temporal limits. To derive time-resolved 3D information, different approaches have been proposed in the literature, but a rigorous comparison among these strategies has not yet been performed. The goal of this study is to quantitatively investigate five published strategies that derive time-resolved volumetric MRI in MRI-guided radiotherapy: Propagation, out-of-plane motion compensation, Fayad model, ROI-based model and Stemkens model. Comparisons were performed using an MRI digital phantom generated with six different patient-derived motion signals and tumour-shapes. An average 4D cycle was generated as well as 2D cine-MRI data with corresponding 3D in-room ground truth. Quantitative analysis was performed by comparing the estimated 3D volume to the ground truth available for each 2D cine-MRI s le. A grouped patient statistical analysis was performed to evaluate the performance of the selected methods, in case of tumour tracking or motion estimation of the whole anatomy. Analyses were also performed based on patient characteristics. Quantitative ranking of the investigated methods highlighted that Propagation and ROI-based model strategies achieved an overall median tumour centre of mass 3D distance from the ground truth of 1.1 mm and 1.3 mm, respectively, and a diaphragm distance below 1.6 mm. Higher errors and variabilities were instead obtained for other methods, which lack the ability to compensate for in-room variations and to account for regional changes. These results were especially evident when further analysing patient characteristics, where errors above 2 mm/5 mm in tumour/diaphragm were found for more irregular breathing patterns in case of out-of-plane motion compensation, Fayad and Stemkens models. These findings suggest the potential of the proposed in silico framework to develop and compare strategies to estimate time-resolved 3DMRI in MRI-guided radiotherapy.
Publisher: Cold Spring Harbor Laboratory
Date: 02-2021
DOI: 10.1101/2021.01.29.21250806
Abstract: Chronic pelvic pain (CPP) is a common condition which significantly impacts the quality of life and wellbeing of many women. Laparoscopy with histopathology is recommended for investigation of pelvic pain and identification of endometriosis with concurrent removal. Never-the-less, the association between endometriosis and pelvic pain is challenging, with endometriosis identified in only 30-50% of women with pain. To explore the predictors for undergoing surgery, for identifying endometriosis and endometriosis severity in a cohort of women with CPP. This study forms part of the Persistent Pelvic Pain project, a prospective observational cohort study (ANZCTR:ACTRN12616000150448). Women referred to a public gynaecology clinic with pain were randomised to one of 2 gynaecology units for routine care and followed for 36-months with 6-monthly surveys assessing demographics, medical history, quality of life, and pain symptoms measured on a Likert scale. Operative notes were reviewed, and endometriosis staged. Of 471 women recruited, 102 women underwent laparoscopy or laparotomy, of whom 52 had endometriosis (n=37 stage I-II n=15 stage III-IV). Gynaecology unit, pelvic pain intensity and lower parity were all predictors of surgery (Odds ratio (OR) 0.342 95%CI 0.209-0.561 OR 1.303 95%CI: 1.079-1.573 OR 0.767 95%CI: 0.620-0.949 respectively). There were no predictors identified for endometriosis diagnosis and the only predictor of severity was increasing age (OR 1.155 95%CI: 1.047-1.310). Pain intensity and gynaecology unit were key predictors of undergoing laparoscopy, however, pain severity did not predict endometriosis diagnosis or staging. These findings indicate the need to review current frameworks guiding practice towards surgery for pelvic pain.
Publisher: IOP Publishing
Date: 05-02-2019
Abstract: In-room magnetic resonance imaging (MRI) allows the acquisition of fast 2D cine-MRI centered in the tumor for advanced motion management in radiotherapy. To achieve 3D information during treatment, patient-specific motion models can be considered the most viable solution. However, conventional global motion models are built using a single motion surrogate, independently from the anatomical location. In this work, we present a novel motion model based on regions of interest (ROIs) established on 4D computed tomography (4DCT) and 2D cine-MRI, aiming at accurately compensating for changes during treatment. In the planning phase, a motion model is built on a 4DCT dataset, through 3D deformable image registration (DIR). ROIs are then defined and correlated with motion fields derived by 2D DIR between CT slices centered in the tumor. In the treatment phase, the model is applied to in-room cine-MRI data to compensate for organ motion in a multi-modal framework, aiming at estimating a time-resolved 3DCT. The method is validated on a digital phantom and tested on two lung patients. Analysis is performed by considering different anatomical planes (coronal, sagittal and a combination of the two) and evaluating the performance of the method on tumor and diaphragm. For the phantom study, the ROI-based model results in a uniform median error on both diaphragm and tumor below 1.5 mm. For what concerns patients, median errors on both diaphragm and tumor are around 2 mm (maximum patient resolution), confirming the capability of the method to regionally compensate for motion. A novel ROI-based motion model is proposed as an integral part of an envisioned clinical MRI-guided workflow aiming at enhanced image guidance compared to conventional strategies.
Publisher: Wiley
Date: 24-05-2021
DOI: 10.1111/AJO.13379
Abstract: Chronic pelvic pain (CPP) is a common condition which significantly impacts the quality of life and wellbeing of many women. Laparoscopy with histopathology is recommended for investigation of pelvic pain and identification of endometriosis with concurrent removal. Never‐the‐less, the association between endometriosis and pelvic pain is challenging, with endometriosis identified in only 30–50% of women with pain. To explore the predictors for undergoing surgery, for identifying endometriosis and endometriosis severity in a cohort of women with CPP. This study forms part of the Persistent Pelvic Pain project, a prospective observational cohort study (ANZCTR:ACTRN12616000150448). Women referred to a public gynaecology clinic with pain were randomised to one of two gynaecology units for routine care and followed for 36 months with 6‐monthly surveys assessing demographics, medical history, quality of life, and pain symptoms measured on a Likert scale. Operative notes were reviewed and endometriosis staged. Of 471 women recruited, 102 women underwent laparoscopy or laparotomy, of whom 52 had endometriosis ( n = 37 stage I–II n = 15 Stage III–IV). Gynaecology unit, pelvic pain intensity and lower parity were all predictors of surgery (odds ratio (OR) 0.342 95% CI 0.209–0.561 OR 1.303 95% CI: 1.079–1.573 OR 0.767 95% CI: 0.620–0.949, respectively). There were no predictors identified for endometriosis diagnosis and the only predictor of severity was increasing age (OR 1.155 95% CI: 1.047–1.310). Gynaecology unit and pain intensity were key predictors of undergoing laparoscopy however, pain severity did not predict endometriosis diagnosis or staging. These findings indicate the need to review current frameworks guiding practice toward surgery for pelvic pain.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2021
No related grants have been discovered for Riccardo Via.