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» Authors » Cristiano Rampinelli

Cristiano Rampinelli

Explore the profile of Cristiano Rampinelli including associated specialties, affiliations and a list of published articles. Areas
Snapshot
Articles 56
Citations 1034
Followers 0
Related Specialties
Oncology
Radiology
Pulmonary Medicine
Top 10 Co-Authors
Massimo Bellomi
Lorenzo Spaggiari
Giulia Veronesi
Patrick Maisonneuve
Raffaella Bertolotti
Sara Raimondi
Monica Casiraghi
Elvio De Fiori
Marta Minotti
Filippo de Marinis
Published In
Cancers (Basel)
Eur Radiol
Radiol Med
Cancer Imaging
J Thorac Oncol
Affiliations
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Recent Articles
1.
Assessment of pulmonary vascular anatomy: comparing augmented reality by holograms versus standard CT images/reconstructions using surgical findings as reference standard
Petrella F, Rizzo S, Rampinelli C, Casiraghi M, Bagnardi V, Frassoni S, et al.
Eur Radiol Exp . 2024 May; 8(1):57. PMID: 38724831
Background: We compared computed tomography (CT) images and holograms (HG) to assess the number of arteries of the lung lobes undergoing lobectomy and assessed easiness in interpretation by radiologists and...
2.
Association between Contrast-Enhanced Computed Tomography Radiomic Features, Genomic Alterations and Prognosis in Advanced Lung Adenocarcinoma Patients
Rinaldi L, Guerini Rocco E, Spitaleri G, Raimondi S, Attili I, Ranghiero A, et al.
Cancers (Basel) . 2023 Sep; 15(18). PMID: 37760521
Non-invasive methods to assess mutational status, as well as novel prognostic biomarkers, are warranted to foster therapy personalization of patients with advanced non-small cell lung cancer (NSCLC). This study investigated...
3.
Impact of image filtering and assessment of volume-confounding effects on CT radiomic features and derived survival models in non-small cell lung cancer
Volpe S, Isaksson L, Zaffaroni M, Pepa M, Raimondi S, Botta F, et al.
Transl Lung Cancer Res . 2023 Jan; 11(12):2452-2463. PMID: 36636424
Background: No evidence supports the choice of specific imaging filtering methodologies in radiomics. As the volume of the primary tumor is a well-recognized prognosticator, our purpose is to assess how...
4.
Low-dose CT for lung cancer screening: position paper from the Italian college of thoracic radiology
Silva M, Picozzi G, Sverzellati N, Anglesio S, Bartolucci M, Cavigli E, et al.
Radiol Med . 2022 Mar; 127(5):543-559. PMID: 35306638
Smoking is the main risk factor for lung cancer (LC), which is the leading cause of cancer-related death worldwide. Independent randomized controlled trials, governmental and inter-governmental task forces, and meta-analyses...
5.
Integrating Biological and Radiological Data in a Structured Repository: a Data Model Applied to the COSMOS Case Study
Garau N, Orro A, Summers P, De Maria L, Bertolotti R, Bassis D, et al.
J Digit Imaging . 2022 Mar; 35(4):970-982. PMID: 35296941
Integrating the information coming from biological samples with digital data, such as medical images, has gained prominence with the advent of precision medicine. Research in this field faces an ever-increasing...
6.
Reproducibility of radiomic features in CT images of NSCLC patients: an integrative analysis on the impact of acquisition and reconstruction parameters
Rinaldi L, de Angelis S, Raimondi S, Rizzo S, Fanciullo C, Rampinelli C, et al.
Eur Radiol Exp . 2022 Jan; 6(1):2. PMID: 35075539
Background: We investigated to what extent tube voltage, scanner model, and reconstruction algorithm affect radiomic feature reproducibility in a single-institution retrospective database of computed tomography images of non-small-cell lung cancer...
7.
A segmentation tool for pulmonary nodules in lung cancer screening: Testing and clinical usage
Garau N, Paganelli C, Summers P, Bassis D, Lanza C, Minotti M, et al.
Phys Med . 2021 Sep; 90:23-29. PMID: 34530212
Purpose: With the future goal of defining a large dataset based on low-dose CT with labelled pulmonary lesions for lung cancer screening (LCS) research, the aim of this work is...
8.
A methodological quality evaluation of the published guidelines and recommendations about the lung cancer screening
Bertolaccini L, Casiraghi M, Petrella F, Rampinelli C, Tessitore A, Spaggiari L
Eur J Cancer Prev . 2021 Sep; 31(1):19-25. PMID: 34519689
Background: A project to assess the existing literature and to benchmark the quality of past guidelines and recommendations on lung cancer screening projects was developed with a particular focus on...
9.
The Challenge of Choosing the Best Classification Method in Radiomic Analyses: Recommendations and Applications to Lung Cancer CT Images
Corso F, Tini G, Lo Presti G, Garau N, De Angelis S, Bellerba F, et al.
Cancers (Basel) . 2021 Jul; 13(12). PMID: 34205631
Radiomics uses high-dimensional sets of imaging features to predict biological characteristics of tumors and clinical outcomes. The choice of the algorithm used to analyze radiomic features and perform predictions has...
10.
Impact of the COVID-19 pandemic on the selection of chest imaging modalities and reporting systems: a survey of Italian radiologists
Borghesi A, Sverzellati N, Polverosi R, Balbi M, Baratella E, Busso M, et al.
Radiol Med . 2021 Jul; 126(10):1258-1272. PMID: 34196908
Purpose: Chest imaging modalities play a key role for the management of patient with coronavirus disease (COVID-19). Unfortunately, there is no consensus on the optimal chest imaging approach in the...