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Article ; Online: Preoperative breast MRI in women with dense breasts: can we keep up with a rapidly changing scenario?

Cozzi, Andrea / Schiaffino, Simone

2023 Volume 33, Issue 11, Page(s) 8077–8079

MeSH term(s)	Female ; Humans ; Breast Neoplasms/diagnostic imaging ; Breast Neoplasms/surgery ; Breast Density ; Mammography ; Breast/diagnostic imaging ; Breast/pathology ; Magnetic Resonance Imaging
Language	English
Publishing date	2023-08-30
Publishing country	Germany
Document type	Editorial ; Comment
ZDB-ID	1085366-2
ISSN	1432-1084 ; 0938-7994 ; 1613-3749
ISSN (online)	1432-1084
ISSN	0938-7994 ; 1613-3749
DOI	10.1007/s00330-023-10075-7
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Article ; Online: Contrast-enhanced mammography-guided biopsy: why, when, and where we need it.

Schiaffino, Simone / Cozzi, Andrea

European radiology

2022

Abstract: Key points: • The use of CEM-guided biopsy is spreading after initial experiences in a few pilot centers.• CEM-guided biopsy has the potential to ensure fast, low-cost, and effective tissue sampling of MRI-detected and CEM-detected lesions that do not ... ...

Abstract	Key points: • The use of CEM-guided biopsy is spreading after initial experiences in a few pilot centers.• CEM-guided biopsy has the potential to ensure fast, low-cost, and effective tissue sampling of MRI-detected and CEM-detected lesions that do not have a corresponding finding at morphological imaging.• The need and utility of CEM-guided biopsy are warranted by the impending expansion of morpho-functional imaging towards breast cancer screening for women with extremely dense breasts.
Language	English
Publishing date	2022-10-31
Publishing country	Germany
Document type	Editorial ; Comment
ZDB-ID	1085366-2
ISSN	1432-1084 ; 0938-7994 ; 1613-3749
ISSN (online)	1432-1084
ISSN	0938-7994 ; 1613-3749
DOI	10.1007/s00330-022-09196-2
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Article: Radiation Dose of Contrast-Enhanced Mammography: A Two-Center Prospective Comparison.

Gennaro, Gisella / Cozzi, Andrea / Schiaffino, Simone / Sardanelli, Francesco / Caumo, Francesca

Cancers

2022 Volume 14, Issue 7

Abstract: The radiation dose associated with contrast-enhanced mammography (CEM) has been investigated only by single-center studies. In this retrospective study, we aimed to compare the radiation dose between two centers performing CEM within two prospective ... ...

Abstract	The radiation dose associated with contrast-enhanced mammography (CEM) has been investigated only by single-center studies. In this retrospective study, we aimed to compare the radiation dose between two centers performing CEM within two prospective studies, using the same type of equipment. The CEM mean glandular dose (MGD) was computed for low energy (LE) and high energy (HE) images and their sum was calculated for each view. MGD and related parameters (entrance dose, breast thickness, compression, and density) were compared between the two centers using the Mann−Whitney test. Finally, per-patient MGD was calculated by pooling the two datasets and determining the contribution of LE and HE images. A total of 348 CEM examinations were analyzed (228 from Center 1 and 120 from Center 2). The median total MGD per view was 2.33 mGy (interquartile range 2.19−2.51 mGy) at Center 1 and 2.46 mGy (interquartile range 2.32−2.70 mGy) at Center 2, with a 0.15 mGy median difference (p < 0.001) equal to 6.2%. LE-images contributed between 64% and 77% to the total patient dose in CEM, with the remaining 23−36% being associated with HE images. The mean radiation dose for a two-view bilateral CEM exam was 4.90 mGy, about 30% higher than for digital mammography.
Language	English
Publishing date	2022-03-31
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2527080-1
ISSN	2072-6694
ISSN	2072-6694
DOI	10.3390/cancers14071774
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Article ; Online: Artificial intelligence for digital breast tomosynthesis: Impact on diagnostic performance, reading times, and workload in the era of personalized screening.

Magni, Veronica / Cozzi, Andrea / Schiaffino, Simone / Colarieti, Anna / Sardanelli, Francesco

European journal of radiology

2022 Volume 158, Page(s) 110631

Abstract: The ultimate goals of the application of artificial intelligence (AI) to digital breast tomosynthesis (DBT) are the reduction of reading times, the increase of diagnostic performance, and the reduction of interval cancer rates. In this review, after ... ...

Abstract	The ultimate goals of the application of artificial intelligence (AI) to digital breast tomosynthesis (DBT) are the reduction of reading times, the increase of diagnostic performance, and the reduction of interval cancer rates. In this review, after outlining the journey from computer-aided detection/diagnosis systems to AI applied to digital mammography (DM), we summarize the results of studies where AI was applied to DBT, noting that long-term advantages of DBT screening and its crucial ability to decrease the interval cancer rate are still under scrutiny. AI has shown the capability to overcome some shortcomings of DBT in the screening setting by improving diagnostic performance and by reducing recall rates (from -2 % to -27 %) and reading times (up to -53 %, with an average 20 % reduction), but the ability of AI to reduce interval cancer rates has not yet been clearly investigated. Prospective validation is needed to assess the cost-effectiveness and real-world impact of AI models assisting DBT interpretation, especially in large-scale studies with low breast cancer prevalence. Finally, we focus on the incoming era of personalized and risk-stratified screening that will first see the application of contrast-enhanced breast imaging to screen women with extremely dense breasts. As the diagnostic advantage of DBT over DM was concentrated in this category, we try to understand if the application of AI to DM in the remaining cohorts of women with heterogeneously dense or non-dense breast could close the gap in diagnostic performance between DM and DBT, thus neutralizing the usefulness of AI application to DBT.
Language	English
Publishing date	2022-12-02
Publishing country	Ireland
Document type	Journal Article
ZDB-ID	138815-0
ISSN	1872-7727 ; 0720-048X
ISSN (online)	1872-7727
ISSN	0720-048X
DOI	10.1016/j.ejrad.2022.110631
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Article ; Online: Immune checkpoint inhibitor-related pneumonitis and COVID-19: a case-matched comparison of CT findings.

Picasso, Riccardo / Cozzi, Andrea / Picasso, Virginia / Zaottini, Federico / Pistoia, Federico / Perissi, Sara / Martinoli, Carlo

La Radiologia medica

2023 Volume 128, Issue 2, Page(s) 212–221

Abstract: Objectives: To compare the radiological findings of immune checkpoint inhibitor-related pneumonitis (IRP) and COVID-19 pneumonia, evaluating the potential of the CO-RADS score to differentiate between them.: Methods: Two readers blindly reviewed ... ...

Abstract	Objectives: To compare the radiological findings of immune checkpoint inhibitor-related pneumonitis (IRP) and COVID-19 pneumonia, evaluating the potential of the CO-RADS score to differentiate between them. Methods: Two readers blindly reviewed chest CTs from age- and sex-matched groups of 33 patients with IRP and 33 patients with COVID-19 pneumonia. Each examiner evaluated the presence of 13 CT features, semiquantitatively scored lung involvement, and assigned a CO-RADS score. Inter-reader reliability in the assessment of CT features and CO-RADS categories was evaluated with Cohen's κ. Distribution differences between groups were evaluated with the χ Results: Substantial or higher inter-reader reliability was found in CO-RADS assignments (κ = 0.664) and in the evaluation of CT features (κ ≥ 0.638), among which the sole feature found to significantly differentiate IRP from COVID-19 pneumonia was unilateral presentation (p < 0.001). Lung involvement semiquantitative scores and CO-RADS scores were significantly higher (p < 0.001) in COVID patients (median involvement score 4, IQR 4-6; median CO-RADS score 5, IQR 4-5) than in IRP patients (median involvement score 2.5, IQR 2-4; median CO-RADS score 3, IQR 3-4) but exploratory analysis of CO-RADS specificity revealed comparatively low values, ranging between 51.5% (Reader 1) and 54.6% (Reader 2). Conclusions: CT features of IRP and COVID-19 pneumonia frequently overlap, save for the extent of lung involvement and bilaterality. In the current SARS-CoV-2 pandemic, the low specificity of the CO-RADS score for the differential diagnosis of COVID-19 pneumonia and IRP may prompt to reconsider the role of imaging in IRP work-up.
MeSH term(s)	Humans ; COVID-19 ; Immune Checkpoint Inhibitors ; SARS-CoV-2 ; Reproducibility of Results ; Tomography, X-Ray Computed/methods ; Pneumonia ; Retrospective Studies
Chemical Substances	Immune Checkpoint Inhibitors
Language	English
Publishing date	2023-01-21
Publishing country	Italy
Document type	Journal Article
ZDB-ID	205751-7
ISSN	1826-6983 ; 0033-8362
ISSN (online)	1826-6983
ISSN	0033-8362
DOI	10.1007/s11547-023-01598-6
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Article ; Online: An update on the management of breast atypical ductal hyperplasia.

Schiaffino, Simone / Cozzi, Andrea / Sardanelli, Francesco

The British journal of radiology

2020 Volume 93, Issue 1110, Page(s) 20200117

Abstract: Among lesions with uncertain malignant potential found at percutaneous breast biopsy, atypical ductal hyperplasia (ADH) carries both the highest risk of underestimation and the closest and most pathologist-dependent differential diagnosis with ductal ... ...

Abstract	Among lesions with uncertain malignant potential found at percutaneous breast biopsy, atypical ductal hyperplasia (ADH) carries both the highest risk of underestimation and the closest and most pathologist-dependent differential diagnosis with ductal carcinoma
MeSH term(s)	Artificial Intelligence ; Biopsy/methods ; Biopsy, Fine-Needle/methods ; Breast/pathology ; Breast/surgery ; Breast Neoplasms/pathology ; Breast Neoplasms/surgery ; Calcinosis/pathology ; Carcinoma, Intraductal, Noninfiltrating/pathology ; Carcinoma, Intraductal, Noninfiltrating/surgery ; Consensus Development Conferences as Topic ; Female ; Humans ; Randomized Controlled Trials as Topic ; Watchful Waiting
Language	English
Publishing date	2020-04-01
Publishing country	England
Document type	Journal Article
ZDB-ID	2982-8
ISSN	1748-880X ; 0007-1285
ISSN (online)	1748-880X
ISSN	0007-1285
DOI	10.1259/bjr.20200117
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Article ; Online: Contrast-enhanced Mammography: A Systematic Review and Meta-Analysis of Diagnostic Performance.

Cozzi, Andrea / Magni, Veronica / Zanardo, Moreno / Schiaffino, Simone / Sardanelli, Francesco

Radiology

2021 Volume 302, Issue 3, Page(s) 568–581

Abstract: Background Contrast-enhanced mammography (CEM) is a promising technique for breast cancer detection, but conflicting results have been reported in previous meta-analyses. Purpose To perform a systematic review and meta-analysis of CEM diagnostic ... ...

Abstract	Background Contrast-enhanced mammography (CEM) is a promising technique for breast cancer detection, but conflicting results have been reported in previous meta-analyses. Purpose To perform a systematic review and meta-analysis of CEM diagnostic performance considering different interpretation methods and clinical settings. Materials and Methods The MEDLINE, EMBASE, Web of Science, and Cochrane Library databases were systematically searched up to July 15, 2021. Prospective and retrospective studies evaluating CEM diagnostic performance with histopathology and/or follow-up as the reference standard were included. Study quality was assessed with the Quality Assessment of Diagnostic Accuracy Studies 2 tool. Summary diagnostic odds ratio and area under the receiver operating characteristic curve were estimated with the hierarchical summary receiver operating characteristic (HSROC) model. Summary estimates of sensitivity and specificity were obtained with the hierarchical bivariate model, pooling studies with the same image interpretation approach or focused on the same findings. Heterogeneity was investigated through meta-regression and subgroup analysis. Results Sixty studies (67 study parts, 11 049 CEM examinations in 10 605 patients) were included. The overall area under the HSROC curve was 0.94 (95% CI: 0.91, 0.96). Pooled diagnostic odds ratio was 55.7 (95% CI: 42.7, 72.7) with high heterogeneity (τ
MeSH term(s)	Breast Neoplasms/diagnostic imaging ; Contrast Media ; Female ; Humans ; Mammography/methods
Chemical Substances	Contrast Media
Language	English
Publishing date	2021-12-14
Publishing country	United States
Document type	Journal Article ; Meta-Analysis ; Systematic Review
ZDB-ID	80324-8
ISSN	1527-1315 ; 0033-8419
ISSN (online)	1527-1315
ISSN	0033-8419
DOI	10.1148/radiol.211412
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Article ; Online: Deep Learning-Based Versus Iterative Image Reconstruction for Unenhanced Brain CT: A Quantitative Comparison of Image Quality.

Cozzi, Andrea / Cè, Maurizio / De Padova, Giuseppe / Libri, Dario / Caldarelli, Nazarena / Zucconi, Fabio / Oliva, Giancarlo / Cellina, Michaela

Tomography (Ann Arbor, Mich.)

2023 Volume 9, Issue 5, Page(s) 1629–1637

Abstract: This exploratory retrospective study aims to quantitatively compare the image quality of unenhanced brain computed tomography (CT) reconstructed with an iterative (AIDR-3D) and a deep learning-based (AiCE) reconstruction algorithm. After a preliminary ... ...

Abstract	This exploratory retrospective study aims to quantitatively compare the image quality of unenhanced brain computed tomography (CT) reconstructed with an iterative (AIDR-3D) and a deep learning-based (AiCE) reconstruction algorithm. After a preliminary phantom study, AIDR-3D and AiCE reconstructions (0.5 mm thickness) of 100 consecutive brain CTs acquired in the emergency setting on the same 320-detector row CT scanner were retrospectively analyzed, calculating image noise reduction attributable to the AiCE algorithm, artifact indexes in the posterior cranial fossa, and contrast-to-noise ratios (CNRs) at the cortical and thalamic levels. In the phantom study, the spatial resolution of the two datasets proved to be comparable; conversely, AIDR-3D reconstructions showed a broader noise pattern. In the human study, median image noise was lower with AiCE compared to AIDR-3D (4.7 vs. 5.3,
MeSH term(s)	Humans ; Retrospective Studies ; Deep Learning ; Tomography, X-Ray Computed ; Brain/diagnostic imaging ; Image Processing, Computer-Assisted
Language	English
Publishing date	2023-08-31
Publishing country	Switzerland
Document type	Journal Article
ISSN	2379-139X
ISSN (online)	2379-139X
DOI	10.3390/tomography9050130
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Article ; Online: Reducing contrast agent residuals in hospital wastewater: the GREENWATER study protocol.

Zanardo, Moreno / Cozzi, Andrea / Cardani, Rosanna / Renna, Laura Valentina / Pomati, Francesco / Asmundo, Luigi / Di Leo, Giovanni / Sardanelli, Francesco

European radiology experimental

2023 Volume 7, Issue 1, Page(s) 27

Abstract: The potential enviromental impact of iodinated (ICAs) and gadolinium-based contrast agents (GBCAs) have recently come under scrutiny, considering the current nonselective wastewater treatment. However, their rapid excretion after intravenous ... ...

Abstract	The potential enviromental impact of iodinated (ICAs) and gadolinium-based contrast agents (GBCAs) have recently come under scrutiny, considering the current nonselective wastewater treatment. However, their rapid excretion after intravenous administration could allow their potential recovery by targeting hospital sewage. The GREENWATER study aims to appraise the effective quantities of ICAs and GBCAs retrievable from patients' urine collected after computed tomography (CT) and magnetic resonance imaging (MRI) exams, selecting ICA/GBCA per-patient urinary excretion and patients' acceptance rate as study endpoints. Within a prospective, observational, single-centre, 1-year framework, we will enrol outpatients aged ≥ 18 years, scheduled to perform contrast-enhanced CT or MRI, willing to collect post-examination urine in dedicated canisters by prolonging their hospital stay to 1 h after injection. Collected urine will be processed and partially stored in the institutional biobank. Patient-based analysis will be performed for the first 100 CT and 100 MRI patients, and then, all analyses will be conducted on the pooled urinary sample. Quantification of urinary iodine and gadolinium will be performed with spectroscopy after oxidative digestion. The evaluation of the acceptance rate will assess the "environmental awareness" of patients and will aid to model how procedures to reduce ICA/GBCA enviromental impact could be adapted in different settings. Key points • Enviromental impact of iodinated and gadolinium-based contrast agents represents a growing point of attention.• Current wastewater treatment is unable to retrieve and recycle contrast agents.• Prolonging hospital stay may allow contrast agents retrieval from patients' urine.• The GREENWATER study will assess the effectively retrievable contrast agents' quantities.• The enrolment acceptance rate will allow to evaluate patients' "green sensitivity".
MeSH term(s)	Humans ; Contrast Media ; Gadolinium/urine ; Hospitals ; Prospective Studies ; Reducing Agents ; Wastewater ; Observational Studies as Topic
Chemical Substances	Contrast Media ; Gadolinium (AU0V1LM3JT) ; Reducing Agents ; Wastewater
Language	English
Publishing date	2023-05-04
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	2509-9280
ISSN (online)	2509-9280
DOI	10.1186/s41747-023-00337-w
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Article: MRI-Conditional Breast Tissue Expander: First In-Human Multi-Case Assessment of MRI-Related Complications and Image Quality.

Schiaffino, Simone / Cozzi, Andrea / Pompei, Barbara / Scarano, Angela Lia / Catanese, Carola / Catic, Armin / Rossi, Lorenzo / Del Grande, Filippo / Harder, Yves

Journal of clinical medicine

2023 Volume 12, Issue 13

Abstract: This study aims to assess potential complications and effects on the magnetic resonance imaging (MRI) image quality of a new MRI-conditional breast tissue expander (Motiva ... ...

Abstract	This study aims to assess potential complications and effects on the magnetic resonance imaging (MRI) image quality of a new MRI-conditional breast tissue expander (Motiva Flora
Language	English
Publishing date	2023-06-30
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2662592-1
ISSN	2077-0383
ISSN	2077-0383
DOI	10.3390/jcm12134410
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