{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,12]],"date-time":"2026-10-12T11:48:43Z","timestamp":1791805723286,"version":"4.3.4"},"reference-count":42,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2023,8,8]],"date-time":"2023-08-08T00:00:00Z","timestamp":1691452800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>The spleen, often referred to as the \u201cforgotten organ\u201d, plays numerous important roles in various diseases. Recently, there has been an increased interest in the application of radiomics in different areas of medical imaging. This systematic review aims to assess the current state of the art and evaluate the methodological quality of radiomics applications in spleen imaging. A systematic search was conducted on PubMed, Scopus, and Web of Science. All the studies were analyzed, and several characteristics, such as year of publication, research objectives, and number of patients, were collected. The methodological quality was evaluated using the radiomics quality score (RQS). Fourteen articles were ultimately included in this review. The majority of these articles were published in non-radiological journals (78%), utilized computed tomography (CT) for extracting radiomic features (71%), and involved not only the spleen but also other organs for feature extraction (71%). Overall, the included papers achieved an average RQS total score of 9.71 \u00b1 6.37, corresponding to an RQS percentage of 27.77 \u00b1 16.04. In conclusion, radiomics applications in spleen imaging demonstrate promising results in various clinical scenarios. However, despite all the included papers reporting positive outcomes, there is a lack of consistency in the methodological approaches employed.<\/jats:p>","DOI":"10.3390\/diagnostics13162623","type":"journal-article","created":{"date-parts":[[2023,8,8]],"date-time":"2023-08-08T12:35:42Z","timestamp":1691498142000},"page":"2623","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Radiomics Applications in Spleen Imaging: A Systematic Review and Methodological Quality Assessment"],"prefix":"10.3390","volume":"13","author":[{"given":"Salvatore Claudio","family":"Fanni","sequence":"first","affiliation":[{"name":"Department of Translational Research, Academic Radiology, University of Pisa, 56126 Pisa, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maria","family":"Febi","sequence":"additional","affiliation":[{"name":"Department of Translational Research, Academic Radiology, University of Pisa, 56126 Pisa, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4161-0193","authenticated-orcid":false,"given":"Roberto","family":"Francischello","sequence":"additional","affiliation":[{"name":"Department of Translational Research, Academic Radiology, University of Pisa, 56126 Pisa, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francesca Pia","family":"Caputo","sequence":"additional","affiliation":[{"name":"Department of Translational Research, Academic Radiology, University of Pisa, 56126 Pisa, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ilaria","family":"Ambrosini","sequence":"additional","affiliation":[{"name":"Department of Translational Research, Academic Radiology, University of Pisa, 56126 Pisa, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9518-9744","authenticated-orcid":false,"given":"Giacomo","family":"Sica","sequence":"additional","affiliation":[{"name":"Radiology Unit, Monaldi Hospital, 80131 Napoli, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5262-4489","authenticated-orcid":false,"given":"Lorenzo","family":"Faggioni","sequence":"additional","affiliation":[{"name":"Department of Translational Research, Academic Radiology, University of Pisa, 56126 Pisa, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Salvatore","family":"Masala","sequence":"additional","affiliation":[{"name":"Department of Medicine, Surgery and Pharmacy, University of Sassari, 07100 Sassari, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michele","family":"Tonerini","sequence":"additional","affiliation":[{"name":"Department of Surgical, Medical, Molecular and Critical Area Pathology, University of Pisa, 56124 Pisa, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mariano","family":"Scaglione","sequence":"additional","affiliation":[{"name":"Department of Medicine, Surgery and Pharmacy, University of Sassari, 07100 Sassari, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5120-886X","authenticated-orcid":false,"given":"Dania","family":"Cioni","sequence":"additional","affiliation":[{"name":"Department of Translational Research, Academic Radiology, University of Pisa, 56126 Pisa, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7950-4559","authenticated-orcid":false,"given":"Emanuele","family":"Neri","sequence":"additional","affiliation":[{"name":"Department of Translational Research, Academic Radiology, University of Pisa, 56126 Pisa, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,8,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"133","DOI":"10.11622\/smedj.2015040","article-title":"Imaging of the spleen: What the clinician needs to know","volume":"56","author":"Vancauwenberghe","year":"2015","journal-title":"Singap. Med. J."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"455","DOI":"10.1080\/01926230600867743","article-title":"Normal Structure, Function, and Histology of the Spleen","volume":"34","author":"Cesta","year":"2006","journal-title":"Toxicol. Pathol."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Rotbain, E.C., Hansen, D.L., De Muckadell, O.S., Wibrand, F., Lund, A.M., and Frederiksen, H. (2017). Splenomegaly\u2014Diagnostic validity, work-up, and underlying causes. PLoS ONE, 12.","DOI":"10.1371\/journal.pone.0186674"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"606","DOI":"10.1038\/nri1669","article-title":"Structure and function of the spleen","volume":"5","author":"Mebius","year":"2005","journal-title":"Nat. Rev. Immunol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1186\/s12967-017-1214-8","article-title":"The spleen in liver cirrhosis: Revisiting an old enemy with novel targets","volume":"15","author":"Li","year":"2017","journal-title":"J. Transl. Med."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"85","DOI":"10.59566\/IJBS.2009.5085","article-title":"Primary Tumors of the Spleen","volume":"5","author":"Fotiadis","year":"2009","journal-title":"Int. J. Biomed. Sci."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"563","DOI":"10.1148\/radiol.2015151169","article-title":"Radiomics: Images are more than pictures, they are data","volume":"278","author":"Gillies","year":"2016","journal-title":"Radiology"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1016\/j.ejca.2011.11.036","article-title":"Radiomics: Extracting more information from medical images using advanced feature analysis","volume":"48","author":"Lambin","year":"2012","journal-title":"Eur. J. Cancer"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"749","DOI":"10.1038\/nrclinonc.2017.141","article-title":"Radiomics: The bridge between medical imaging and personalized medicine","volume":"14","author":"Lambin","year":"2017","journal-title":"Nat. Rev. Clin. Oncol."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Aringhieri, G., Fanni, S.C., Febi, M., Colligiani, L., Cioni, D., and Neri, E. (2022). The Role of Radiomics in Salivary Gland Imaging: A Systematic Review and Radiomics Quality Assessment. Diagnostics, 12.","DOI":"10.3390\/diagnostics12123002"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Candita, G., Rossi, S., Cwiklinska, K., Fanni, S.C., Cioni, D., Lencioni, R., and Neri, E. (2023). Imaging Diagnosis of Hepatocellular Carcinoma: A State-of-the-Art Review. Diagnostics, 13.","DOI":"10.3390\/diagnostics13040625"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1143256","DOI":"10.3389\/fnume.2023.1143256","article-title":"Radiomics insight into the neurodegenerative \u2018hot\u2019 brain: A narrative review from the nuclear medicine perspective","volume":"3","author":"Aghakhanyan","year":"2023","journal-title":"Front. Nucl. Med."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1141499","DOI":"10.3389\/fradi.2023.1141499","article-title":"A first look into radiomics application in testicular imaging: A systematic review","volume":"3","author":"Fanni","year":"2023","journal-title":"Front. Radiol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1186\/s13244-023-01365-1","article-title":"Systematic review with radiomics quality score of cholangiocarcinoma: An EuSoMII Radiomics Auditing Group Initiative","volume":"14","author":"Cannella","year":"2023","journal-title":"Insights Imaging"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2239","DOI":"10.1007\/s00330-022-09180-w","article-title":"Ovarian imaging radiomics quality score assessment: An EuSoMII radiomics auditing group initiative","volume":"33","author":"Ponsiglione","year":"2022","journal-title":"Eur. Radiol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"R150","DOI":"10.1088\/0031-9155\/61\/13\/R150","article-title":"Applications and limitations of radiomics","volume":"61","author":"Yip","year":"2016","journal-title":"Phys. Med. Biol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"3","DOI":"10.4274\/balkanmedj.galenos.2022.2022-11-51","article-title":"Must-have Qualities of Clinical Research on Artificial Intelligence and Machine Learning","volume":"40","author":"Cuocolo","year":"2023","journal-title":"Balkan Med. J."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"n71","DOI":"10.1136\/bmj.n71","article-title":"The PRISMA 2020 statement: An updated guideline for reporting systematic reviews","volume":"372","author":"Page","year":"2021","journal-title":"BMJ"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1186\/s13643-016-0384-4","article-title":"Rayyan-a web and mobile app for systematic reviews","volume":"5","author":"Ouzzani","year":"2016","journal-title":"Syst. Rev."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"972","DOI":"10.3906\/sag-2009-270","article-title":"Evaluation of systemic involvement of coronavirus disease 2019 through spleen; size and texture analysis","volume":"51","author":"Batur","year":"2021","journal-title":"Turk. J. Med. Sci."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Enke, J.S., Moltz, J.H., D\u2019Anastasi, M., Kunz, W.G., Schmidt, C., Maurus, S., M\u00fchlberg, A., Katzmann, A., S\u00fchling, M., and Hahn, H. (2022). Radiomics Features of the Spleen as Surrogates for CT-Based Lymphoma Diagnosis and Subtype Differentiation. Cancers, 14.","DOI":"10.3390\/cancers14030713"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"15041","DOI":"10.1109\/ACCESS.2021.3052776","article-title":"A Multi-Organ Fusion and LightGBM Based Radiomics Algorithm for High-Risk Esophageal Varices Prediction in Cirrhotic Patients","volume":"9","author":"Li","year":"2021","journal-title":"IEEE Access"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"716849","DOI":"10.3389\/fonc.2021.716849","article-title":"Spleen Radiomics Signature: A Potential Biomarker for Prediction of Early and Late Recurrences of Hepatocellular Carcinoma After Resection","volume":"11","author":"Li","year":"2021","journal-title":"Front. Oncol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1076","DOI":"10.3748\/wjg.v29.i6.1076","article-title":"Clinical-radiomics nomogram for predicting esophagogastric variceal bleeding risk noninvasively in patients with cirrhosis","volume":"29","author":"Luo","year":"2023","journal-title":"World J. Gastroenterol."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"745931","DOI":"10.3389\/fmed.2021.745931","article-title":"CT-Based Radiomics Score Can Accurately Predict Esophageal Variceal Rebleeding in Cirrhotic Patients","volume":"8","author":"Meng","year":"2021","journal-title":"Front. Med."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1007\/s11548-020-02295-9","article-title":"MRI-based radiomic feature analysis of end-stage liver disease for severity stratification","volume":"16","author":"Nitsch","year":"2021","journal-title":"Int. J. Comput. Assist. Radiol. Surg."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"682456","DOI":"10.3389\/fonc.2021.682456","article-title":"Establishment of the Radiologic Tumor Invasion Index Based on Radiomics Splenic Features and Clinical Factors to Predict Serous Invasion of Gastric Cancer","volume":"11","author":"Pan","year":"2021","journal-title":"Front. Oncol."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Sack, J., Nitsch, J., Meine, H., Kikinis, R., Halle, M., and Rutherford, A. (2022). Quantitative Analysis of Liver Disease Using MRI-Based Radiomic Features of the Liver and Spleen. J. Imaging, 8.","DOI":"10.3390\/jimaging8100277"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"108927","DOI":"10.1016\/j.ejrad.2020.108927","article-title":"Application of CT-based radiomics in predicting portal pressure and patient outcome in portal hypertension","volume":"126","author":"Tseng","year":"2020","journal-title":"Eur. J. Radiol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1932","DOI":"10.1016\/j.ejso.2020.06.021","article-title":"Use of radiomics to extract splenic features to predict prognosis of patients with gastric cancer","volume":"46","author":"Wang","year":"2020","journal-title":"Eur. J. Surg. Oncol."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"423","DOI":"10.1007\/s12072-021-10292-6","article-title":"A novel machine learning-based radiomic model for diagnosing high bleeding risk esophagea varices in cirrhotic patients","volume":"16","author":"Yan","year":"2022","journal-title":"Hepatol. Int."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"792677","DOI":"10.3389\/fmed.2021.792677","article-title":"Development and Validation of a Nomogram Based on 18F-FDG PET\/CT Radiomics to Predict the Overall Survival in Adult Hemophagocytic Lymphohistiocytosis","volume":"8","author":"Yang","year":"2021","journal-title":"Front. Med."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Yin, Y., Yakar, D., Dierckx, R.A.J.O., Mouridsen, K.B., Kwee, T.C., and de Haas, R.J. (2022). Combining Hepatic and Splenic CT Radiomic Features Improves Radiomic Analysis Performance for Liver Fibrosis Staging. Diagnostics, 12.","DOI":"10.3390\/diagnostics12020550"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1167602","DOI":"10.3389\/fonc.2023.1167602","article-title":"Are Radiomic Spleen Features Useful Assess. Differ. Status Adv. Gastric Cancer?","volume":"13","author":"Lyu","year":"2023","journal-title":"Front. Oncol."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"507","DOI":"10.5858\/arpa.2020-0802-RA","article-title":"Hemophagocytic Lymphohistiocytosis","volume":"146","author":"Ponnatt","year":"2022","journal-title":"Arch. Pathol. Lab. Med."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"909455","DOI":"10.3389\/fpubh.2022.909455","article-title":"The Burden of Liver Cirrhosis in Mortality: Results from the Global Burden of Disease Study","volume":"10","author":"Ye","year":"2022","journal-title":"Front. Public Heal."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"2050","DOI":"10.1111\/liv.14555","article-title":"Radiomics in liver diseases: Current progress and future opportunities","volume":"40","author":"Wei","year":"2020","journal-title":"Liver Int."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1336","DOI":"10.4254\/wjh.v8.i31.1336","article-title":"Mortality and Rebleeding Following Variceal Haemorrhage in Liver Cirrhosis and Periportal Fibrosis","volume":"8","author":"Mohammed","year":"2016","journal-title":"World J. Hepatol."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1186\/s41747-023-00334-z","article-title":"A multicenter evaluation of a deep learning software (LungQuant) for lung parenchyma characterization in COVID-19 pneumonia","volume":"7","author":"Scapicchio","year":"2023","journal-title":"Eur. Radiol. Exp."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"4314","DOI":"10.1007\/s00330-021-08485-6","article-title":"Lung vessel volume evaluated with CALIPER software is an independent predictor of mortality in COVID-19 patients: A multicentric retrospective analysis","volume":"32","author":"Romei","year":"2022","journal-title":"Eur. Radiol."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"105467","DOI":"10.1016\/j.compbiomed.2022.105467","article-title":"COVID-19 prognostic modeling using CT radiomic features and machine learning algorithms: Analysis of a multi-institutional dataset of 14,339 patients: COVID-19 prognostic modeling using CT radiomics and machine learning","volume":"145","author":"Shiri","year":"2022","journal-title":"Comput. Biol. Med."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/j.gtc.2022.10.006","article-title":"Diagnostic and Therapeutic Radiology of the GI Tract, Liver, and Pancreas in Patients with COVID","volume":"52","author":"Boraschi","year":"2023","journal-title":"Gastroenterol. Clin. North Am."}],"container-title":["Diagnostics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2075-4418\/13\/16\/2623\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T20:28:07Z","timestamp":1760128087000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2075-4418\/13\/16\/2623"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8,8]]},"references-count":42,"journal-issue":{"issue":"16","published-online":{"date-parts":[[2023,8]]}},"alternative-id":["diagnostics13162623"],"URL":"https:\/\/doi.org\/10.3390\/diagnostics13162623","relation":{},"ISSN":["2075-4418"],"issn-type":[{"value":"2075-4418","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,8,8]]}}}