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Rubio IT, Wyld L, Marotti L, Athanasiou A, Regitnig P, Catanuto G, Schoones JW, Zambon M, Camps J, Santini D, Dietz J, Sardanelli F, Varga Z, Smidt M, Sharma N, Shaaban AM, Gilbert F. European guidelines for the diagnosis, treatment and follow-up of breast lesions with uncertain malignant potential (B3 lesions) developed jointly by EUSOMA, EUSOBI, ESP (BWG) and ESSO. EUROPEAN JOURNAL OF SURGICAL ONCOLOGY 2024; 50:107292. [PMID: 38061151 DOI: 10.1016/j.ejso.2023.107292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Accepted: 11/17/2023] [Indexed: 01/16/2024]
Abstract
INTRODUCTION Breast lesions of uncertain malignant potential (B3) include atypical ductal and lobular hyperplasias, lobular carcinoma in situ, flat epithelial atypia, papillary lesions, radial scars and fibroepithelial lesions as well as other rare miscellaneous lesions. They are challenging to categorise histologically, requiring specialist training and multidisciplinary input. They may coexist with in situ or invasive breast cancer (BC) and increase the risk of subsequent BC development. Management should focus on adequate classification and management whilst avoiding overtreatment. The aim of these guidelines is to provide updated information regarding the diagnosis and management of B3 lesions, according to updated literature review evidence. METHODS These guidelines provide practical recommendations which can be applied in clinical practice which include recommendation grade and level of evidence. All sections were written according to an updated literature review and discussed at a consensus meeting. Critical appraisal by the expert writing committee adhered to the 23 items in the international Appraisal of Guidelines, Research and Evaluation (AGREE) tool. RESULTS Recommendations for further management after core-needle biopsy (CNB) or vacuum-assisted biopsy (VAB) diagnosis of a B3 lesion reported in this guideline, vary depending on the presence of atypia, size of lesion, sampling size, and patient preferences. After CNB or VAB, the option of vacuum-assisted excision or surgical excision should be evaluated by a multidisciplinary team and shared decision-making with the patient is crucial for personalizing further treatment. De-escalation of surgical intervention for B3 breast lesions is ongoing, and the inclusion of vacuum-assisted excision (VAE) will decrease the need for surgical intervention in further approaches. Communication with patients may be different according to histological diagnosis, presence or absence of atypia, or risk of upgrade due to discordant imaging. Written information resources to help patients understand these issues alongside with verbal communication is recommended. Lifestyle interventions have a significant impact on BC incidence so lifestyle interventions need to be suggested to women at increased BC risk as a result of a diagnosis of a B3 lesion. CONCLUSIONS These guidelines provide a state-of-the-art overview of the diagnosis, management and prognosis of B3 lesions in modern multidisciplinary breast practice.
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Affiliation(s)
- Isabel T Rubio
- Breast Surgical Oncology, Clinica Universidad de Navarra, Madrid, Spain; European Society of Breast Cancer Specialists (EUSOMA), Florence, Italy; European Society of Surgical Oncology (ESSO), Brussels, Belgium.
| | - Lynda Wyld
- Department of Oncology and Metabolism, University of Sheffield Medical School, Beech Hill Road, Sheffield, S10 2RX, UK; Doncaster and Bassetlaw Teaching Hospitals NHS Foundation Trust, Doncaster, UK
| | - Lorenza Marotti
- European Society of Breast Cancer Specialists (EUSOMA), Florence, Italy
| | | | - Peter Regitnig
- Diagnostic and Research Institute of Pathology, Medical University of Graz, Graz, Austria
| | - Giuseppe Catanuto
- Humanitas-Istituto Clinico Catanese Misterbianco, Italy; Fondazione G.Re.T.A., ETS, Napoli, Italy
| | - Jan W Schoones
- Research Policy & Graduate School Advisor, Leiden University Medical Center Leiden, the Netherlands
| | - Marzia Zambon
- Europa Donna - The European Breast Cancer Coalition, Milan, Italy
| | - Julia Camps
- Breast Health Units in Ribera Salud Hospitals.Valencia, Spain
| | - Donatella Santini
- Department of Pathology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Italy
| | - Jill Dietz
- The American Society of Breast Surgeons, Columbia, MD, USA
| | - Francesco Sardanelli
- Department of Biomedical Sciences for Health, Università Degli Studi di Milano, Milan, Italy; Unit of Radiology, IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy
| | - Zsuzsanna Varga
- Department of Pathology and Molecular Pathology, University Hospital Zurich, Zurich, Switzerland
| | - Marjolein Smidt
- GROW-School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht, the Netherlands; Department of Surgery, Maastricht University Medical Centre, Maastricht, the Netherlands
| | - Nisha Sharma
- Breast Unit, Level 1 Chancellor Wing, St James Hospital, Beckett Street Leeds, West Yorkshire, LS9 7TF, UK
| | - Abeer M Shaaban
- Cellular Pathology, Queen Elizabeth Hospital Birmingham, Birmingham, UK; Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
| | - Fiona Gilbert
- Department of Radiology, University of Cambridge, Cambridge Biomedical Campus, UK.
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Miceli R, Mercado CL, Hernandez O, Chhor C. Active Surveillance for Atypical Ductal Hyperplasia and Ductal Carcinoma In Situ. JOURNAL OF BREAST IMAGING 2023; 5:396-415. [PMID: 38416903 DOI: 10.1093/jbi/wbad026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Indexed: 03/01/2024]
Abstract
Atypical ductal hyperplasia (ADH) and ductal carcinoma in situ (DCIS) are relatively common breast lesions on the same spectrum of disease. Atypical ductal hyperblasia is a nonmalignant, high-risk lesion, and DCIS is a noninvasive malignancy. While a benefit of screening mammography is early cancer detection, it also leads to increased biopsy diagnosis of noninvasive lesions. Previously, treatment guidelines for both entities included surgical excision because of the risk of upgrade to invasive cancer after surgery and risk of progression to invasive cancer for DCIS. However, this universal management approach is not optimal for all patients because most lesions are not upgraded after surgery. Furthermore, some DCIS lesions do not progress to clinically significant invasive cancer. Overtreatment of high-risk lesions and DCIS is considered a burden on patients and clinicians and is a strain on the health care system. Extensive research has identified many potential histologic, clinical, and imaging factors that may predict ADH and DCIS upgrade and thereby help clinicians select which patients should undergo surgery and which may be appropriate for active surveillance (AS) with imaging. Additionally, multiple clinical trials are currently underway to evaluate whether AS for DCIS is feasible for a select group of patients. Recent advances in MRI, artificial intelligence, and molecular markers may also have an important role to play in stratifying patients and delineating best management guidelines. This review article discusses the available evidence regarding the feasibility and limitations of AS for ADH and DCIS, as well as recent advances in patient risk stratification.
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Affiliation(s)
- Rachel Miceli
- NYU Langone Health, Department of Radiology, New York, NY, USA
| | | | | | - Chloe Chhor
- NYU Langone Health, Department of Radiology, New York, NY, USA
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Fraker JL, Clune CG, Sahni SK, Yaganti A, Vegunta S. Prevalence, Impact, and Diagnostic Challenges of Benign Breast Disease: A Narrative Review. Int J Womens Health 2023; 15:765-778. [PMID: 37223067 PMCID: PMC10202205 DOI: 10.2147/ijwh.s351095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 05/05/2023] [Indexed: 05/25/2023] Open
Abstract
Benign breast diseases, which are commonly seen in clinical practice, have various clinical presentations and implications, as well as management strategies. This article describes common benign breast lesions, presentations of these lesions, and typical radiographic and histologic findings. Also included in this review are the most recent data and guideline-based recommendations for the management of benign breast diseases at diagnosis, including surgical referral, medical management, and ongoing surveillance.
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Affiliation(s)
- Jessica L Fraker
- Division of Women’s Health Internal Medicine, Mayo Clinic, Scottsdale, AZ, USA
| | - Caroline G Clune
- Center for Breast Care, Mayo Clinic Health System — Southwest Wisconsin Region, La Crosse, WI, USA
- Division of General Internal Medicine, Mayo Clinic, Rochester, MN, USA
| | - Sabrina K Sahni
- Jacoby Center for Breast Health, Mayo Clinic, Jacksonville, FL, USA
| | - Avani Yaganti
- Southern Illinois University School of Medicine, Springfield, IL, USA
| | - Suneela Vegunta
- Division of Women’s Health Internal Medicine, Mayo Clinic, Scottsdale, AZ, USA
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Prediction of Prednisolone Dose Correction Using Machine Learning. JOURNAL OF HEALTHCARE INFORMATICS RESEARCH 2023; 7:84-103. [PMID: 36910914 PMCID: PMC9995628 DOI: 10.1007/s41666-023-00128-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 11/20/2022] [Accepted: 02/03/2023] [Indexed: 02/17/2023]
Abstract
Wrong dose, a common prescription error, can cause serious patient harm, especially in the case of high-risk drugs like oral corticosteroids. This study aims to build a machine learning model to predict dose-related prescription modifications for oral prednisolone tablets (i.e., highly imbalanced data with very few positive cases). Prescription data were obtained from the electronic medical records at a single institute. Cluster analysis classified the clinical departments into six clusters with similar patterns of prednisolone prescription. Two patterns of training datasets were created with/without preprocessing by the SMOTE method. Five ML models (SVM, KNN, GB, RF, and BRF) and logistic regression (LR) models were constructed by Python. The model was internally validated by five-fold stratified cross-validation and was validated with a 30% holdout test dataset. Eighty-two thousand five hundred fifty-three prescribing data for prednisolone tablets containing 135 dose-corrected positive cases were obtained. In the original dataset (without SMOTE), only the BRF model showed a good performance (in test dataset, ROC-AUC:0.917, recall: 0.951). In the training dataset preprocessed by SMOTE, performance was improved on all models. The highest performance models with SMOTE were SVM (in test dataset, ROC-AUC: 0.820, recall: 0.659) and BRF (ROC-AUC: 0.814, recall: 0.634). Although the prescribing data for dose-related collection are highly imbalanced, various techniques such as the following have allowed us to build high-performance prediction models: data preprocessing by SMOTE, stratified cross-validation, and BRF classifier corresponding to imbalanced data. ML is useful in complicated dose audits such as oral prednisolone. Supplementary Information The online version contains supplementary material available at 10.1007/s41666-023-00128-3.
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Lo Gullo R, Vincenti K, Rossi Saccarelli C, Gibbs P, Fox MJ, Daimiel I, Martinez DF, Jochelson MS, Morris EA, Reiner JS, Pinker K. Diagnostic value of radiomics and machine learning with dynamic contrast-enhanced magnetic resonance imaging for patients with atypical ductal hyperplasia in predicting malignant upgrade. Breast Cancer Res Treat 2021; 187:535-545. [PMID: 33471237 PMCID: PMC8190021 DOI: 10.1007/s10549-020-06074-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Accepted: 12/23/2020] [Indexed: 02/03/2023]
Abstract
Purpose To investigate whether radiomics features extracted from magnetic resonance imaging (MRI) of patients with biopsy-proven atypical ductal hyperplasia (ADH) coupled with machine learning can differentiate high-risk lesions that will upgrade to malignancy at surgery from those that will not, and to determine if qualitatively and semi-quantitatively assessed imaging features, clinical factors, and image-guided biopsy technical factors are associated with upgrade rate. Methods This retrospective study included 127 patients with 139 breast lesions yielding ADH at biopsy who were assessed with multiparametric MRI prior to biopsy. Two radiologists assessed all lesions independently and with a third reader in consensus according to the BI-RADS lexicon. Univariate analysis and multivariate modeling were performed to identify significant radiomic features to be included in a machine learning model to discriminate between lesions that upgraded to malignancy on surgery from those that did not. Results Of 139 lesions, 28 were upgraded to malignancy at surgery, while 111 were not upgraded. Diagnostic accuracy was 53.6%, specificity 79.2%, and sensitivity 15.3% for the model developed from pre-contrast features, and 60.7%, 86%, and 22.8% for the model developed from delta radiomics datasets. No significant associations were found between any radiologist-assessed lesion parameters and upgrade status. There was a significant correlation between the number of specimens sampled during biopsy and upgrade status (p = 0.003). Conclusion Radiomics analysis coupled with machine learning did not predict upgrade status of ADH. The only significant result from this analysis is between the number of specimens sampled during biopsy procedure and upgrade status at surgery.
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Affiliation(s)
- Roberto Lo Gullo
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, 300 E 66th Street, New York, NY, 10065, USA
| | - Kerri Vincenti
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, 300 E 66th Street, New York, NY, 10065, USA
| | - Carolina Rossi Saccarelli
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, 300 E 66th Street, New York, NY, 10065, USA
| | - Peter Gibbs
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 300 E 66th Street, New York, NY, 10065, USA
| | - Michael J Fox
- Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, Mortimer B. Zuckerman Research Center, 417 E 68th Street, New York, NY, 10065, USA
| | - Isaac Daimiel
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, 300 E 66th Street, New York, NY, 10065, USA
| | - Danny F Martinez
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, 300 E 66th Street, New York, NY, 10065, USA
| | - Maxine S Jochelson
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, 300 E 66th Street, New York, NY, 10065, USA
| | - Elizabeth A Morris
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, 300 E 66th Street, New York, NY, 10065, USA
| | - Jeffrey S Reiner
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, 300 E 66th Street, New York, NY, 10065, USA
| | - Katja Pinker
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, 300 E 66th Street, New York, NY, 10065, USA. .,Department of Biomedical Imaging and Image-guided Therapy, Division of Molecular and Structural Preclinical Imaging, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria.
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Abstract
High-risk breast lesions (HRLs) are a group of heterogeneous lesions that can be associated with a synchronous or adjacent breast cancer and that confer an elevated lifetime risk of breast cancer. Management of HRLs after core needle biopsy may include close imaging and clinical follow-up or excisional biopsy to evaluate for cancer. This article reviews histologic features and clinical presentation of each of the HRLs, current evidence with regard to management, and guidelines from the American Society of Breast Surgeons and National Comprehensive Cancer Network. In addition, imaging surveillance and risk-reduction strategies for women with HRLs are discussed.
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Uzan C, Mazouni C, Rossoni C, De Korvin B, de Lara CT, Cohen M, Chabbert N, Zilberman S, Boussion V, Vincent Salomon A, Espie M, Coutant C, Marchal F, Salviat F, Boulanger L, Doutriaux-Dumoulin I, Jouve E, Mathelin C, de Saint Hilaire P, Mollard J, Balleyguier C, Joyon N, Triki ML, Delaloge S, Michiels S. Prospective Multicenter Study Validate a Prediction Model for Surgery Uptake Among Women with Atypical Breast Lesions. Ann Surg Oncol 2020; 28:2138-2145. [PMID: 32920723 DOI: 10.1245/s10434-020-09107-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Accepted: 08/18/2020] [Indexed: 12/20/2022]
Abstract
BACKGROUND Diagnosis of atypical breast lesions (ABLs) leads to unnecessary surgery in 75-90% of women. We have previously developed a model including age, complete radiological target excision after biopsy, and focus size that predicts the probability of cancer at surgery. The present study aimed to validate this model in a prospective multicenter setting. - METHODS Women with a recently diagnosed ABL on image-guided biopsy were recruited in 18 centers, before wire-guided localized excisional lumpectomy. Primary outcome was the negative predictive value (NPV) of the model. RESULTS The NOMAT model could be used in 287 of the 300 patients included (195 with ADH). At surgery, 12 invasive (all grade 1), and 43 in situ carcinomas were identified (all ABL: 55/287, 19%; ADH only: 49/195, 25%). The area under the receiving operating characteristics curve of the model was 0.64 (95% CI 0.58-0.69) for all ABL, and 0.63 for ADH only (95% CI 0.56-0.70). For the pre-specified threshold of 20% predicted probability of cancer, NPV was 82% (77-87%) for all ABL, and 77% (95% CI 71-83%) for patients with ADH. At a 10% threshold, NPV was 89% (84-94%) for all ABL, and 85% (95% CI 78--92%) for the ADH. At this threshold, 58% of the whole ABL population (and 54% of ADH patients) could have avoided surgery with only 2 missed invasive cancers. CONCLUSION The NOMAT model could be useful to avoid unnecessary surgery among women with ABL, including for patients with ADH. CLINICAL TRIAL REGISTRATION NCT02523612.
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Affiliation(s)
- Catherine Uzan
- AP-HP (Assistance Publique des Hôpitaux de Paris), Department of Gynecological and Breast Surgery and Oncology, Pitié-Salpêtrière University Hospital, Paris, France. .,Sorbonne University, INSERM UMR_S_938, "Cancer Biology and Therapeutics", Centre de Recherche Saint-Antoine (CRSA), Paris, France. .,Institut Universitaire de Cancérologie (IUC), Paris, France.
| | | | | | | | | | | | | | | | | | - Anne Vincent Salomon
- Institut Curie, Université Paris-Sciences Lettres, INSERM U934, Département de Médecine Diagnostique et Théranostique, Paris, France
| | - Marc Espie
- University of Paris, Hôpital Saint Louis, APHP, Paris, France
| | | | - Frederic Marchal
- Institut de Cancérologie de Lorraine, Vandœuvre-lès-Nancy, France
| | - Flore Salviat
- Service de Biostatistique et d'Épidémiologie, Gustave Roussy, Villejuif, France.,CESP INSERM U1018, Université Paris-Sud, Université Paris-Saclay, Villejuif, France
| | | | | | - Eva Jouve
- Institut Claudius Regaud-Oncopole, Toulouse, France
| | - Carole Mathelin
- Les Hôpitaux universitaires de Strasbourg, Strasbourg, France
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Schiaffino S, Calabrese M, Melani EF, Trimboli RM, Cozzi A, Carbonaro LA, Di Leo G, Sardanelli F. Upgrade Rate of Percutaneously Diagnosed Pure Atypical Ductal Hyperplasia: Systematic Review and Meta-Analysis of 6458 Lesions. Radiology 2019; 294:76-86. [PMID: 31660803 DOI: 10.1148/radiol.2019190748] [Citation(s) in RCA: 47] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Background Management of percutaneously diagnosed pure atypical ductal hyperplasia (ADH) is an unresolved clinical issue. Purpose To calculate the pooled upgrade rate of percutaneously diagnosed pure ADH. Materials and Methods A search of MEDLINE and EMBASE databases was performed in October 2018. Preferred Reporting Items for Systematic Reviews and Meta-Analyses, or PRISMA, guidelines were followed. A fixed- or random-effects model was used, along with subgroup and meta-regression analyses. The Newcastle-Ottawa scale was used for study quality, and the Egger test was used for publication bias. Results Of 521 articles, 93 were analyzed, providing data for 6458 ADHs (5911 were managed with surgical excision and 547 with follow-up). Twenty-four studies used core-needle biopsy; 44, vacuum-assisted biopsy; 21, both core-needle and vacuum-assisted biopsy; and four, unspecified techniques. Biopsy was performed with stereotactic guidance in 29 studies; with US guidance in nine, with MRI guidance in nine, and with mixed guidance in eight. Overall heterogeneity was high (I2 = 80%). Subgroup analysis according to management yielded a pooled upgrade rate of 29% (95% confidence interval [CI]: 26%, 32%) for surgically excised lesions and 5% (95% CI: 4%, 8%) for lesions managed with follow-up (P < .001). Heterogeneity was entirely associated with surgically excised lesions (I2 = 78%) rather than those managed with follow-up (I2 = 0%). Most variability was explained by guidance and needle caliper (P = .15). At subgroup analysis of surgically excised lesions, the pooled upgrade rate was 42% (95% CI: 31%, 53%) for US guidance, 23% (95% CI: 19%, 27%) for stereotactic biopsy, and 32% (95% CI: 22%, 43%) for MRI guidance, with heterogeneity (52%, 63%, and 56%, respectively) still showing the effect of needle caliper. When the authors considered patients with apparent complete lesion removal after biopsy (subgroups in 14 studies), the pooled upgrade rate was 14% (95% CI: 8%, 23%). Study quality was low to medium; the risk of publication bias was low (P = .10). Conclusion Because of a pooled upgrade rate higher than 2% (independent of biopsy technique, needle size, imaging guidance, and apparent complete lesion removal), atypical ductal hyperplasia diagnosed with percutaneous needle biopsy should be managed with surgical excision. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Brem in this issue.
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Affiliation(s)
- Simone Schiaffino
- From the Unit of Radiology, IRCCS Policlinico San Donato, San Donato Milanese, Italy (S.S., L.A.C., G.D.L., F.S.); Unit of Radiology, IRCCS Policlinico San Martino, Genoa, Italy (M.C.); Unit of Radiology, Ente Ospedaliero Ospedali Galliera, Genoa, Italy (E.F.M.); and Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133 Milan, Italy (R.M.T., A.C., F.S.)
| | - Massimo Calabrese
- From the Unit of Radiology, IRCCS Policlinico San Donato, San Donato Milanese, Italy (S.S., L.A.C., G.D.L., F.S.); Unit of Radiology, IRCCS Policlinico San Martino, Genoa, Italy (M.C.); Unit of Radiology, Ente Ospedaliero Ospedali Galliera, Genoa, Italy (E.F.M.); and Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133 Milan, Italy (R.M.T., A.C., F.S.)
| | - Enrico Francesco Melani
- From the Unit of Radiology, IRCCS Policlinico San Donato, San Donato Milanese, Italy (S.S., L.A.C., G.D.L., F.S.); Unit of Radiology, IRCCS Policlinico San Martino, Genoa, Italy (M.C.); Unit of Radiology, Ente Ospedaliero Ospedali Galliera, Genoa, Italy (E.F.M.); and Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133 Milan, Italy (R.M.T., A.C., F.S.)
| | - Rubina Manuela Trimboli
- From the Unit of Radiology, IRCCS Policlinico San Donato, San Donato Milanese, Italy (S.S., L.A.C., G.D.L., F.S.); Unit of Radiology, IRCCS Policlinico San Martino, Genoa, Italy (M.C.); Unit of Radiology, Ente Ospedaliero Ospedali Galliera, Genoa, Italy (E.F.M.); and Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133 Milan, Italy (R.M.T., A.C., F.S.)
| | - Andrea Cozzi
- From the Unit of Radiology, IRCCS Policlinico San Donato, San Donato Milanese, Italy (S.S., L.A.C., G.D.L., F.S.); Unit of Radiology, IRCCS Policlinico San Martino, Genoa, Italy (M.C.); Unit of Radiology, Ente Ospedaliero Ospedali Galliera, Genoa, Italy (E.F.M.); and Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133 Milan, Italy (R.M.T., A.C., F.S.)
| | - Luca Alessandro Carbonaro
- From the Unit of Radiology, IRCCS Policlinico San Donato, San Donato Milanese, Italy (S.S., L.A.C., G.D.L., F.S.); Unit of Radiology, IRCCS Policlinico San Martino, Genoa, Italy (M.C.); Unit of Radiology, Ente Ospedaliero Ospedali Galliera, Genoa, Italy (E.F.M.); and Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133 Milan, Italy (R.M.T., A.C., F.S.)
| | - Giovanni Di Leo
- From the Unit of Radiology, IRCCS Policlinico San Donato, San Donato Milanese, Italy (S.S., L.A.C., G.D.L., F.S.); Unit of Radiology, IRCCS Policlinico San Martino, Genoa, Italy (M.C.); Unit of Radiology, Ente Ospedaliero Ospedali Galliera, Genoa, Italy (E.F.M.); and Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133 Milan, Italy (R.M.T., A.C., F.S.)
| | - Francesco Sardanelli
- From the Unit of Radiology, IRCCS Policlinico San Donato, San Donato Milanese, Italy (S.S., L.A.C., G.D.L., F.S.); Unit of Radiology, IRCCS Policlinico San Martino, Genoa, Italy (M.C.); Unit of Radiology, Ente Ospedaliero Ospedali Galliera, Genoa, Italy (E.F.M.); and Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133 Milan, Italy (R.M.T., A.C., F.S.)
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