Massimo Castellani

1.3k total citations
77 papers, 843 citations indexed

About

Massimo Castellani is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Surgery. According to data from OpenAlex, Massimo Castellani has authored 77 papers receiving a total of 843 indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Radiology, Nuclear Medicine and Imaging, 25 papers in Pulmonary and Respiratory Medicine and 14 papers in Surgery. Recurrent topics in Massimo Castellani's work include Medical Imaging Techniques and Applications (17 papers), Radiomics and Machine Learning in Medical Imaging (15 papers) and Radiopharmaceutical Chemistry and Applications (8 papers). Massimo Castellani is often cited by papers focused on Medical Imaging Techniques and Applications (17 papers), Radiomics and Machine Learning in Medical Imaging (15 papers) and Radiopharmaceutical Chemistry and Applications (8 papers). Massimo Castellani collaborates with scholars based in Italy, Switzerland and United States. Massimo Castellani's co-authors include Paolo Gerundini, Eugenio Reschini, Luigia Florimonte, Angelo Castello, Virgilio Longari, Luca Urso, A. Paracchi, Luca Giovanella, Corrado Cittanti and Luca Ceriani and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Gastroenterology.

In The Last Decade

Massimo Castellani

72 papers receiving 834 citations

Peers

Massimo Castellani
Anton Staudenherz Austria
Amol Takalkar United States
Ömer Uğur Türkiye
Jong Jin Lee South Korea
Manlio Cabria Italy
Sait Sağer Türkiye
Angela M. Riddell United Kingdom
Masatoyo Nakajo Japan
Eun Young Kim South Korea
Homer Macapinlac United States
Anton Staudenherz Austria
Massimo Castellani
Citations per year, relative to Massimo Castellani Massimo Castellani (= 1×) peers Anton Staudenherz

Countries citing papers authored by Massimo Castellani

Since Specialization
Citations

This map shows the geographic impact of Massimo Castellani'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 Massimo Castellani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Massimo Castellani more than expected).

Fields of papers citing papers by Massimo Castellani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Massimo Castellani. 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 Massimo Castellani. The network helps show where Massimo Castellani may publish in the future.

Co-authorship network of co-authors of Massimo Castellani

This figure shows the co-authorship network connecting the top 25 collaborators of Massimo Castellani. A scholar is included among the top collaborators of Massimo Castellani 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 Massimo Castellani. Massimo Castellani 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
1.
Castello, Angelo, Lorenzo Rosso, Giorgio Alberto Croci, et al.. (2025). Machine Learning Models Derived from [18F]FDG PET/CT for the Prediction of Recurrence in Patients with Thymomas. Bioengineering. 12(7). 721–721.
2.
Urso, Luca, Angelo Castello, Alessandro Crestani, et al.. (2025). The Role of Radiomics and Artificial Intelligence Applied to Staging PSMA PET in Assessing Prostate Cancer Aggressiveness. Journal of Clinical Medicine. 14(10). 3318–3318. 3 indexed citations
3.
Castello, Angelo, et al.. (2024). Prognostic Role of PSMA-Targeted Imaging in Metastatic Castration-Resistant Prostate Cancer: An Overview. Biomedicines. 12(10). 2355–2355. 2 indexed citations
4.
Ciarmiello, Andrea, Elisabetta Giovannini, Amalia Milano, et al.. (2024). Does FDG PET-Based Radiomics Have an Added Value for Prediction of Overall Survival in Non-Small Cell Lung Cancer?. Journal of Clinical Medicine. 13(9). 2613–2613. 4 indexed citations
5.
6.
Castello, Angelo, Luca Urso, Maria Cristina Marzola, et al.. (2023). Comparison of MRI vs. [18F]FDG PET/CT for Treatment Response Evaluation of Primary Breast Cancer after Neoadjuvant Chemotherapy: Literature Review and Future Perspectives. Journal of Clinical Medicine. 12(16). 5355–5355. 4 indexed citations
7.
Castello, Angelo, Domenico Albano, Barbara Muoio, et al.. (2023). Diagnostic Accuracy of PET with 18F-Fluciclovine ([18F]FACBC) in Detecting High-Grade Gliomas: A Systematic Review and Meta-Analysis. Diagnostics. 13(24). 3610–3610. 7 indexed citations
8.
Urso, Luca, Alberto Nieri, Angelo Castello, et al.. (2023). The Role of Molecular Imaging in Patients with Brain Metastases: A Literature Review. Cancers. 15(7). 2184–2184. 3 indexed citations
9.
Urso, Luca, Angelo Castello, Giorgio Treglia, et al.. (2023). Relevance of Volumetric Parameters Applied to [68Ga]Ga-DOTATOC PET/CT in NET Patients Treated with PRRT. Diagnostics. 13(4). 606–606. 4 indexed citations
10.
Urso, Luca, Alberto Nieri, Licia Uccelli, et al.. (2023). Lutathera® Orphans: State of the Art and Future Application of Radioligand Therapy with 177Lu-DOTATATE. Pharmaceutics. 15(4). 1110–1110. 22 indexed citations
11.
Urso, Luca, Luca Filippi, Angelo Castello, et al.. (2023). PSMA PET/CT in Castration-Resistant Prostate Cancer: Myth or Reality?. Journal of Clinical Medicine. 12(22). 7130–7130. 9 indexed citations
12.
Urso, Luca, Angelo Castello, Stefano Panareo, et al.. (2022). Role of PSMA-ligands imaging in Renal Cell Carcinoma management: current status and future perspectives. Journal of Cancer Research and Clinical Oncology. 148(6). 1299–1311. 38 indexed citations
13.
Urso, Luca, Angelo Castello, Laura Evangelista, et al.. (2022). PET-Derived Radiomics and Artificial Intelligence in Breast Cancer: A Systematic Review. International Journal of Molecular Sciences. 23(21). 13409–13409. 39 indexed citations
14.
Castello, Angelo, Luca Urso, Licia Uccelli, et al.. (2022). The Role of [68Ga]PSMA PET/CT for Clinical Suspicion of Prostate Cancer in Patients with or without Previous Negative Biopsy: A Systematic Review. Cancers. 14(20). 5036–5036. 11 indexed citations
15.
Florimonte, Luigia, et al.. (2022). 918P Improving TNM staging predictive value with PET/CT imaging features and deep learning model in non-small cell lung cancer. Annals of Oncology. 33. S966–S966. 1 indexed citations
16.
Ciarmiello, Andrea, Luigia Florimonte, Claudia Bareggi, et al.. (2021). 1137P Machine learning radiomics for prediction of survival in non-small cell lung cancer patients studied with PET/CT and FDG. Annals of Oncology. 32. S926–S926. 1 indexed citations
17.
18.
Florimonte, Luigia, et al.. (2016). 18F-Choline PET/CT-Positive Lytic Bone Lesions in Prostate Cancer and Accidental Myeloma Detection. Clinical Nuclear Medicine. 41(5). 394–396. 5 indexed citations
19.
Castellani, Massimo, Virgilio Longari, Rosaria Giordano, et al.. (2007). 13N-NH3 PET: The assessment of myocardial perfusion in patients with AMI and stem cell therapy. 48(7). 1226–1226.
20.
Castellani, Massimo, Eugenio Reschini, A. Bruno, et al.. (1996). Incidental Finding of Accessory Spleen on Bone Scintigraphy. Clinical Nuclear Medicine. 21(12). 967–967. 1 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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