Riccardo De Robertis

Dr. Riccardo De Robertis

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Research Focus & Metrics

Academic Career Length

18Years (2009-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 July 2015 in American Journal of Roentgenology
Verified
Journal Article
Closed access
Mirko D'OnofrioMirko D'Onofrio
Mirko D'Onofrio
SCStefano Crosara
Stefano Crosara
RRRiccardo De Robertis
Riccardo De Robertis
SCStefano Canestrini
Stefano Canestrini
RMRoberto Pozzi Mucelli
Roberto Pozzi Mucelli
The purpose of this article is to discuss the use of contrast-enhanced ultra-sound (CEUS) in focal liver lesions. Focal liver lesions are usually detected incidentally during abdominal ultrasound. The injection of microbubble ultrasound contrast agents improves the characterization of focal liver lesions that are indeterminate on conventional ultrasound. The use of CEUS is recommended in official guidelines and suggested as a second diagnostic step after ultrasound detection of indeterminate focal liver lesions to immediately establish the diagnosis, especially for benign liver lesions, such as hemangiomas, avoiding further and more expensive examinations.

8 June 2020 in Cancers
Verified
Journal Article
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CMCarmelo Messina
Carmelo Messina
RBRodolfo Bignone
Rodolfo Bignone
ABAlberto Bruno
Alberto Bruno
ABAntonio Bruno
Antonio Bruno
Federico BrunoFederico Bruno
Federico Bruno
OGon behalf of the Young SIRM Working Group
on behalf of the Young SIRM Working Group
To date, diffusion weighted imaging (DWI) is included in routine magnetic resonance imaging (MRI) protocols for several cancers. The real additive role of DWI lies in the “functional” information obtained by probing the free diffusivity of water molecules into intra and inter-cellular spaces that in tumors mainly depend on cellularity. Although DWI has not gained much space in some oncologic scenarios, this non-invasive tool is routinely used in clinical practice and still remains a hot research topic: it has been tested in almost all cancers to differentiate malignant from benign lesions, to distinguish different malignant histotypes or tumor grades, to predict and/or assess treatment responses, and to identify residual or recurrent tumors in follow-up examinations. In this review, we provide an up-to-date overview on the application of DWI in oncology.

19 January 2018 in European Radiology
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Journal Article
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RRRiccardo De Robertis
Riccardo De Robertis
BMBogdan Maris
Bogdan Maris
NCNicolò Cardobi
Nicolò Cardobi
PMPaolo Tinazzi Martini
Paolo Tinazzi Martini
SGStefano Gobbo
Stefano Gobbo
MDMirko D’oNofrio
Mirko D’oNofrio

18 February 2019 in Scientific Reports
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Journal Article
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Mirko D'OnofrioMirko D'Onofrio
Mirko D'Onofrio
VCValentina Ciaravino
Valentina Ciaravino
NCNicolò Cardobi
Nicolò Cardobi
RRRiccardo De Robertis
Riccardo De Robertis
SCSara Cingarlini
Sara Cingarlini
ASAldo Scarpa
Aldo Scarpa
To evaluate pancreatic neuroendocrine neoplasms (panNENs) grade prediction by means of qualitative and quantitative CT evaluation, and 3D CT-texture analysis. Patients with histopathologically-proven panNEN, availability of Ki67% values and pre-treatment CT were included. CT images were retrospectively reviewed, and qualitative and quantitative images analysis were done; for quantitative analysis four enhancement-ratios and three permeability-ratios were created. 3D CT-texture imaging analysis was done (Mean Value; Variance; Skewness; Kurtosis; Entropy). Subsequently, these features were compared among the three grading (G) groups. 304 patients affected by panNENs were considered, and 100 patients were included. At qualitative evaluation, frequency of irregular margins was significantly different between tumor G groups. At quantitative evaluation, for all ratios, comparisons resulted statistical significant different between G1 and G3 groups and between G2 and G3 groups. At 3D CT-texture analysis, Kurtosis resulted statistical significant different among three G groups and Entropy resulted statistical significant different between G1 and G3 and between G2 and G3 groups. Quantitative CT evaluation of panNENs can predict tumor grade, discerning G1 from G3 and G2 from G3 tumors. CT-texture analysis can predict panNENs tumor grade, distinguishing G1 from G3 and G2 from G3, and G1 from G2 tumors.

27 November 2018 in Neuroendocrinology
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Journal Article
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GMGiovanni Marchegiani
Giovanni Marchegiani
LLLuca Landoni
Luca Landoni
SAStefano Andrianello
Stefano Andrianello
GMGaia Masini
Gaia Masini
SCSara Cingarlini
Sara Cingarlini
CBClaudio Bassi
Claudio Bassi
Background/Aims: Pancreatic neuroendocrine tumors (pan-NENs) represent an increasingly common indication for pancreatic resection, but there are few data regarding possible recurrence after surgery. The aim of the study was to describe the frequency, timing, and patterns of recurrence after resection for pan-NENs with consequent implications for postoperative follow-up. Methods: We performed a retrospective analysis of pan-NENs resected between 1990 and 2015 at The Pancreas Institute, University of Verona Hospital Trust. Predictors of recurrence were assessed. Survival analysis was conducted using the Kaplan-Meier and conditional survival (CS) methods. Results: The cohort consisted of 487 patients with a median follow-up of 71 months. Recurrence developed in 12.3%: 54 (11.1%) liver metastases, 11 (2.3%) local recurrence, 10 (2.1%) nodal recurrence, and 8 (1.6%) metastases in other organs. Thirty-one (6.4%) died due to disease recurrence. Size > 21 mm, G3 grade, nodal metastasis, and vascular infiltration were independent predictors of overall recurrence. Recurrence occurred either during the first year of follow-up (n = 9), or after 10 years (n = 4). CS analysis revealed that nonfunctioning G1 pan-NEN ≤20 mm without nodal metastasis or vascular invasion had a negligible risk of developing recurrence. In the present series, after 5 years of follow-up without developing recurrence, tumor recurrence occurred only in the form of liver metastases. Conclusions: Recurrence of pan-NENs is rare and is predicted by tumor size, nodal metastasis, grading, and vascular invasion. Patients with G1 pan-NEN without nodal metastasis and vascular invasion may be considered cured by surgery. After 5 years without recurrence, follow-up should focus on excluding the development of liver metastases.

1 January 2015 in World Journal of Radiology
Verified
Journal Article
Open access
RRRiccardo De Robertis
Riccardo De Robertis
PMPaolo Tinazzi Martini
Paolo Tinazzi Martini
EDEmanuele Demozzi
Emanuele Demozzi
FCFlavia Dal Corso
Flavia Dal Corso
CBClaudio Bassi
Claudio Bassi
Mirko D'OnofrioMirko D'Onofrio
Mirko D'Onofrio
Magnetic resonance imaging (MRI) is a reliable and accurate imaging method for the evaluation of patients with pancreatic ductal adenocarcinoma (PDAC). Diffusion-weighted imaging (DWI) is a relatively recent technological improvement that expanded MRI capabilities, having brought functional aspects into conventional morphologic MRI evaluation. DWI can depict the random diffusion of water molecules within tissues (the so-called Brownian motions). Modifications of water diffusion induced by different factors acting on the extracellular and intracellular spaces, as increased cell density, edema, fibrosis, or altered functionality of cell membranes, can be detected using this MR sequence. The intravoxel incoherent motion (IVIM) model is an advanced DWI technique that consent a separate quantitative evaluation of all the microscopic random motions that contribute to DWI, which are essentially represented by molecular diffusion and blood microcirculation (perfusion). Technological improvements have made possible the routine use of DWI during abdominal MRI study. Several authors have reported that the addition of DWI sequence can be of value for the evaluation of patients with PDAC, especially improving the staging; nevertheless, it is still unclear whether and how DWI could be helpful for identification, characterization, prognostic stratification and follow-up during treatment. The aim of this paper is to review up-to-date literature data regarding the applications of DWI and IVIM to PDACs.