Gaetano Paone

1.8k total citations
74 papers, 1.2k citations indexed

About

Gaetano Paone is a scholar working on Radiology, Nuclear Medicine and Imaging, Surgery and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Gaetano Paone has authored 74 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Radiology, Nuclear Medicine and Imaging, 27 papers in Surgery and 26 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Gaetano Paone's work include Thyroid Cancer Diagnosis and Treatment (24 papers), Radiopharmaceutical Chemistry and Applications (11 papers) and Radiomics and Machine Learning in Medical Imaging (11 papers). Gaetano Paone is often cited by papers focused on Thyroid Cancer Diagnosis and Treatment (24 papers), Radiopharmaceutical Chemistry and Applications (11 papers) and Radiomics and Machine Learning in Medical Imaging (11 papers). Gaetano Paone collaborates with scholars based in Switzerland, Italy and France. Gaetano Paone's co-authors include Corinne Haïoun, Jehan Dupuis, Emmanuel Itti, Alain Rahmouni, Luca Giovanella, Michel Meignan, Luca Ceriani, Chieh Lin, Alain Luciani and Chia-Hung Lin and has published in prestigious journals such as Journal of Clinical Oncology, Blood and The Journal of Clinical Endocrinology & Metabolism.

In The Last Decade

Gaetano Paone

63 papers receiving 1.2k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Gaetano Paone Switzerland 16 660 595 342 289 267 74 1.2k
Hubert H. Chuang United States 19 340 0.5× 311 0.5× 413 1.2× 88 0.3× 255 1.0× 52 1.2k
Lucia Rampin Italy 22 745 1.1× 166 0.3× 441 1.3× 488 1.7× 669 2.5× 85 1.8k
M. J. OʼDoherty United Kingdom 15 600 0.9× 216 0.4× 519 1.5× 108 0.4× 300 1.1× 38 1.3k
Giovanni Bosio Italy 20 398 0.6× 274 0.5× 295 0.9× 138 0.5× 199 0.7× 53 994
Anne Lerberg Nielsen Denmark 15 379 0.6× 329 0.6× 256 0.7× 56 0.2× 173 0.6× 46 957
Anton Staudenherz Austria 17 263 0.4× 130 0.2× 247 0.7× 81 0.3× 456 1.7× 62 1.1k
Homer Macapinlac United States 10 466 0.7× 150 0.3× 370 1.1× 294 1.0× 339 1.3× 21 1.2k
Yasemin Şanlı Türkiye 19 472 0.7× 108 0.2× 328 1.0× 131 0.5× 368 1.4× 86 1.4k
Sherif Heiba United States 17 344 0.5× 138 0.2× 150 0.4× 121 0.4× 410 1.5× 67 982
Luca Vaggelli Italy 13 262 0.4× 270 0.5× 473 1.4× 28 0.1× 163 0.6× 24 862

Countries citing papers authored by Gaetano Paone

Since Specialization
Citations

This map shows the geographic impact of Gaetano Paone's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Gaetano Paone with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gaetano Paone more than expected).

Fields of papers citing papers by Gaetano Paone

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gaetano Paone. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Gaetano Paone. The network helps show where Gaetano Paone may publish in the future.

Co-authorship network of co-authors of Gaetano Paone

This figure shows the co-authorship network connecting the top 25 collaborators of Gaetano Paone. A scholar is included among the top collaborators of Gaetano Paone based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Gaetano Paone. Gaetano Paone is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
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Muoio, Barbara, Davide Giovanni Bosetti, Maddalena Sansovini, et al.. (2025). Peptide Receptor Radionuclide Therapy in Patients with Advanced, Recurrent or Progressive Meningioma: An Updated Systematic Review and Meta-Analysis. Cancers. 17(12). 2039–2039.
3.
Cuzzocrea, Marco, Rosa Di Micco, Stefania Rizzo, et al.. (2025). The Role of [18F]FES PET/CT in Breast Cancer Management: An Umbrella Review. Cancers. 17(10). 1644–1644.
4.
Muoio, Barbara, Domenico Albano, Alessio Rizzo, et al.. (2025). The Prevalence and Significance of Incidental Positron Emission Tomography Findings in the Brain Using Radiotracers Other than [18F]FDG: A Systematic Review and Meta-Analysis. Diagnostics. 15(10). 1204–1204. 1 indexed citations
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Albano, Domenico, Alessio Rizzo, Arnoldo Piccardo, et al.. (2025). Meta-Analysis on the Prevalence and Significance of Incidental Findings in the Thyroid Gland Using Other PET Radiopharmaceuticals Beyond [18F]FDG. Pharmaceuticals. 18(5). 723–723. 1 indexed citations
7.
Bosetti, Davide Giovanni, et al.. (2024). “Rosary Sign” at Somatostatin Receptor PET in a Case of Recurrent Meningioma. Diagnostics. 14(22). 2608–2608. 1 indexed citations
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Laudicella, Riccardo, Matteo Bauckneht, Alexander Maurer, et al.. (2023). Can We Predict Skeletal Lesion on Bone Scan Based on Quantitative PSMA PET/CT Features?. Cancers. 15(22). 5471–5471. 2 indexed citations
10.
Giovanella, Luca, Maria Luisa Garo, Marco Cuzzocrea, Gaetano Paone, & Ken Herrmann. (2023). Prognostic role of early prostate specific antigen changes after [177Lu]Lu‐PSMA radioligand therapy of metastasized prostate cancer: A meta‐analysis. European Journal of Clinical Investigation. 53(9). e14014–e14014. 6 indexed citations
11.
Ceriani, Luca, Lisa Milan, Camilla Virili, et al.. (2020). Radiomics Analysis of [ 18 F]-Fluorodeoxyglucose-Avid Thyroid Incidentalomas Improves Risk Stratification and Selection for Clinical Assessment. Thyroid. 31(1). 88–95. 25 indexed citations
12.
Trimboli, Pierpaolo, Giorgio Treglia, Arnoldo Piccardo, et al.. (2020). FNA indication according to ACR-TIRADS, EU-TIRADS and K-TIRADS in thyroid incidentalomas at 18F-FDG PET/CT. Journal of Endocrinological Investigation. 43(11). 1607–1612. 11 indexed citations
13.
Piccardo, Arnoldo, Pierpaolo Trimboli, Matteo Puntoni, et al.. (2019). Role of 18 F-Choline Positron Emission Tomography/Computed Tomography to Detect Structural Relapse in High-Risk Differentiated Thyroid Cancer Patients. Thyroid. 29(4). 549–556. 11 indexed citations
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Trimboli, Pierpaolo, Gaetano Paone, Giorgio Treglia, et al.. (2018). Fine‐needle aspiration in all thyroid incidentalomas at 18F‐FDG PET/CT: Can EU‐TIRADS revise the dogma?. Clinical Endocrinology. 89(5). 642–648. 16 indexed citations
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Giovanella, Luca, Arnoldo Piccardo, Gaetano Paone, et al.. (2013). Thyroid lobe ablation with iodine-131 in patients with differentiated thyroid carcinoma. Nuclear Medicine Communications. 34(8). 767–770. 15 indexed citations
18.
Lin, Chieh, Emmanuel Itti, Alain Luciani, et al.. (2011). Whole-Body Diffusion-Weighted Imaging With Apparent Diffusion Coefficient Mapping for Treatment Response Assessment in Patients With Diffuse Large B-Cell Lymphoma. Investigative Radiology. 46(5). 341–349. 62 indexed citations
19.
Lin, Chia-Hung, Emmanuel Itti, Corinne Haïoun, et al.. (2007). Early 18F-FDG PET for Prediction of Prognosis in Patients with Diffuse Large B-Cell Lymphoma: SUV-Based Assessment Versus Visual Analysis. Journal of Nuclear Medicine. 48(10). 1626–1632. 299 indexed citations
20.
Storto, Giovanni, Michele Klain, Gaetano Paone, et al.. (2006). Combined therapy of Sr-89 and zoledronic acid in patients with painful bone metastases. Bone. 39(1). 35–41. 45 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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