{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,21]],"date-time":"2026-07-21T02:38:21Z","timestamp":1784601501558,"version":"3.55.0"},"reference-count":24,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T00:00:00Z","timestamp":1761782400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T00:00:00Z","timestamp":1761782400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/501100006065","name":"Department of Health, Government of Western Australia","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100006065","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Radiol med"],"DOI":"10.1007\/s11547-025-02137-1","type":"journal-article","created":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T07:10:56Z","timestamp":1761808256000},"page":"320-331","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Deep learning-based PSMA PET segmentation repeatability: A post-hoc analysis of a single-center, prospective, test\u2013retest trial"],"prefix":"10.1007","volume":"131","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6524-539X","authenticated-orcid":false,"given":"Jake","family":"Kendrick","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Roslyn J.","family":"Francis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ghulam Mubashar","family":"Hassan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jeremy S. L.","family":"Ong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robert","family":"Jeraj","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nathaniel","family":"Barry","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Martin A.","family":"Ebert","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,10,30]]},"reference":[{"key":"2137_CR1","first-page":"229","volume":"74","author":"F Bray","year":"2024","unstructured":"Bray F, Laversanne M, Sung H et al (2024) Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 74:229\u2013263","journal-title":"CA Cancer J Clin"},{"key":"2137_CR2","doi-asserted-by":"publisher","first-page":"4835","DOI":"10.1091\/mbc.e02-11-0731","volume":"14","author":"SA Rajasekaran","year":"2003","unstructured":"Rajasekaran SA, Anilkumar G, Oshima E et al (2003) A novel cytoplasmic tail MXXXL motif mediates the internalization of prostate-specific membrane antigen. Mol Biol Cell 14:4835\u20134845","journal-title":"Mol Biol Cell"},{"key":"2137_CR3","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.233460","volume":"312","author":"PH Kuo","year":"2024","unstructured":"Kuo PH, Morris MJ, Hesterman J et al (2024) Quantitative 68Ga-PSMA-11 PET and clinical outcomes in metastatic castration-resistant prostate cancer following 177Lu-PSMA-617 (VISION trial). Radiology 312:e233460","journal-title":"Radiology"},{"key":"2137_CR4","doi-asserted-by":"publisher","first-page":"1389","DOI":"10.1016\/S1470-2045(22)00605-2","volume":"23","author":"JP Buteau","year":"2022","unstructured":"Buteau JP, Martin AJ, Emmett L et al (2022) PSMA and FDG-PET as predictive and prognostic biomarkers in patients given [177Lu]Lu-PSMA-617 versus cabazitaxel for metastatic castration-resistant prostate cancer (TheraP): a biomarker analysis from a randomised, open-label, phase 2 trial. Lancet Oncol 23:1389\u20131397","journal-title":"Lancet Oncol"},{"key":"2137_CR5","doi-asserted-by":"publisher","DOI":"10.2967\/jnumed.121.263072","author":"A Gafita","year":"2022","unstructured":"Gafita A, Rauscher I, Weber M et al (2022) Novel framework for treatment response evaluation using PSMA-PET\/CT in patients with metastatic castration-resistant prostate cancer (RECIP 1.0): an international multicenter study. J Nucl Med. https:\/\/doi.org\/10.2967\/jnumed.121.263072","journal-title":"J Nucl Med"},{"key":"2137_CR6","doi-asserted-by":"publisher","DOI":"10.2967\/jnumed.123.267234","author":"A Gafita","year":"2024","unstructured":"Gafita A, Djaileb L, Rauscher I et al (2024) RECIP 1.0 predicts progression-free survival after [177Lu]Lu-PSMA radiopharmaceutical therapy in patients with metastatic castration-resistant prostate cancer. J Nucl Med. https:\/\/doi.org\/10.2967\/jnumed.123.267234","journal-title":"J Nucl Med"},{"key":"2137_CR7","doi-asserted-by":"crossref","unstructured":"Gafita A, Rauscher I, Fendler WP, et al. (2022) Measuring response in metastatic castration-resistant prostate cancer using PSMA PET\/CT: comparison of RECIST 1.1, aPCWG3, aPERCIST, PPP, and RECIP 1.0 criteria. Eur J Nucl Med Mol Imaging.","DOI":"10.1007\/s00259-022-05882-x"},{"key":"2137_CR8","doi-asserted-by":"publisher","DOI":"10.1007\/s00259-023-06382-2","author":"J Kendrick","year":"2023","unstructured":"Kendrick J, Francis RJ, Hassan GM et al (2023) Prognostic utility of RECIP 1.0 with manual and AI-based segmentations in biochemically recurrent prostate cancer from [68Ga]Ga-PSMA-11 PET images. Eur J Nucl Med Mol Imaging. https:\/\/doi.org\/10.1007\/s00259-023-06382-2","journal-title":"Eur J Nucl Med Mol Imaging"},{"key":"2137_CR9","doi-asserted-by":"publisher","first-page":"1041","DOI":"10.1007\/s00259-021-05497-8","volume":"49","author":"K Johnsson","year":"2022","unstructured":"Johnsson K, Brynolfsson J, Sahlstedt H et al (2022) Analytical performance of aPROMISE: automated anatomic contextualization, detection, and quantification of [18F]DCFPyL (PSMA) imaging for standardized reporting. Eur J Nucl Med Mol Imaging 49:1041\u20131051","journal-title":"Eur J Nucl Med Mol Imaging"},{"key":"2137_CR10","doi-asserted-by":"publisher","DOI":"10.1007\/s00259-022-05927-1","author":"J Kendrick","year":"2022","unstructured":"Kendrick J, Francis RJ, Hassan GM, Rowshanfarzad P, Ong JS, Ebert MA (2022) Fully automatic prognostic biomarker extraction from metastatic prostate lesion segmentations in whole-body [68Ga] Ga-PSMA-11 PET\/CT images. Eur J Nucl Med Mol Imaging. https:\/\/doi.org\/10.1007\/s00259-022-05927-1","journal-title":"Eur J Nucl Med Mol Imaging"},{"key":"2137_CR11","doi-asserted-by":"publisher","first-page":"67S","DOI":"10.2967\/jnumed.116.186767","volume":"58","author":"M Eiber","year":"2017","unstructured":"Eiber M, Fendler WP, Rowe SP et al (2017) Prostate-specific membrane antigen ligands for imaging and therapy. J Nucl Med 58:67S-76S","journal-title":"J Nucl Med"},{"key":"2137_CR12","doi-asserted-by":"publisher","first-page":"678","DOI":"10.1007\/s00259-016-3573-4","volume":"44","author":"FL Giesel","year":"2016","unstructured":"Giesel FL, Hadaschik B, Cardinale J et al (2016) F-18 labelled PSMA-1007: biodistribution, radiation dosimetry and histopathological validation of tumor lesions in prostate cancer patients. Eur J Nucl Med Mol Imaging 44:678\u2013688","journal-title":"Eur J Nucl Med Mol Imaging"},{"key":"2137_CR13","doi-asserted-by":"publisher","DOI":"10.1259\/bjr.20221178","volume":"96","author":"J Kendrick","year":"2023","unstructured":"Kendrick J, Francis RJ, Hassan GM et al (2023) Prospective inter- and intra-tracer repeatability analysis of radiomics features in [68 Ga]Ga-PSMA-11 and [18 F]F-PSMA-1007 PET scans in metastatic prostate cancer. Br J Radiol 96:20221178","journal-title":"Br J Radiol"},{"key":"2137_CR14","doi-asserted-by":"publisher","first-page":"1320","DOI":"10.2967\/jnumed.119.236075","volume":"61","author":"BHE Jansen","year":"2020","unstructured":"Jansen BHE, Cysouw MCF, Vis AN et al (2020) Repeatability of quantitative 18 f-DCFPyL PET\/CT measurements in metastatic prostate cancer. J Nucl Med 61:1320","journal-title":"J Nucl Med"},{"key":"2137_CR15","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2022\/7056983","volume":"2022","author":"RA Werner","year":"2022","unstructured":"Werner RA, Habacha B, L\u00fctje S et al (2022) High SUVs Have More Robust Repeatability in Patients with Metastatic Prostate Cancer: Results from a Prospective Test-Retest Cohort Imaged with 18F-DCFPyL. Mol Imaging 2022:1\u201310","journal-title":"Mol Imaging"},{"key":"2137_CR16","doi-asserted-by":"publisher","first-page":"1145","DOI":"10.2967\/jnumed.119.236083","volume":"61","author":"JH Pollard","year":"2020","unstructured":"Pollard JH, Raman C, Zakharia Y et al (2020) Quantitative test-retest measurement of 68Ga-PSMA-HBED-CC in tumor and normal tissue. J Nucl Med 61:1145\u20131152","journal-title":"J Nucl Med"},{"key":"2137_CR17","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1038\/s41592-020-01008-z","volume":"18","author":"F Isensee","year":"2021","unstructured":"Isensee F, Jaeger PF, Kohl SAA, Petersen J, Maier-Hein KH (2021) Nnu-net: a self-configuring method for deep learning-based biomedical image segmentation. Nat Methods 18:203\u2013211","journal-title":"Nat Methods"},{"key":"2137_CR18","doi-asserted-by":"publisher","first-page":"405","DOI":"10.1016\/j.eururo.2023.02.002","volume":"83","author":"R Seifert","year":"2023","unstructured":"Seifert R, Emmett L, Rowe SP et al (2023) Second version of the Prostate Cancer Molecular Imaging Standardized Evaluation Framework including Response Evaluation for Clinical Trials (PROMISE V2). Eur Urol 83:405\u2013412","journal-title":"Eur Urol"},{"key":"2137_CR19","doi-asserted-by":"publisher","first-page":"678","DOI":"10.2967\/jnumed.119.233817","volume":"61","author":"S Fanti","year":"2020","unstructured":"Fanti S, Hadaschik B, Herrmann K (2020) Proposal for systemic-therapy response-assessment criteria at the time of PSMA PET\/CT imaging: the PSMA PET progression criteria. J Nucl Med 61:678\u2013682","journal-title":"J Nucl Med"},{"key":"2137_CR20","doi-asserted-by":"publisher","DOI":"10.1016\/j.clgc.2024.102155","author":"M Dell'Oro","year":"2024","unstructured":"Dell\u2019Oro M, Huff DT, Lokre O et al (2024) Assessing the heterogeneity of response of [68Ga] Ga-PSMA-11 PET\/CT lesions in patients with biochemical recurrence of prostate cancer. Clin Genitourin Cancer. https:\/\/doi.org\/10.1016\/j.clgc.2024.102155","journal-title":"Clin Genitourin Cancer"},{"key":"2137_CR21","doi-asserted-by":"publisher","first-page":"302","DOI":"10.1053\/j.semnuclmed.2019.02.008","volume":"49","author":"H-J Wester","year":"2019","unstructured":"Wester H-J, Schottelius M (2019) PSMA-targeted radiopharmaceuticals for imaging and therapy. Semin Nucl Med 49:302\u2013312","journal-title":"Semin Nucl Med"},{"key":"2137_CR22","doi-asserted-by":"publisher","first-page":"763","DOI":"10.1007\/s00259-021-05520-y","volume":"49","author":"DA Pattison","year":"2021","unstructured":"Pattison DA, Debowski M, Gulhane B et al (2021) Prospective intra-individual blinded comparison of [18F]PSMA-1007 and [68 Ga]Ga-PSMA-11 PET\/CT imaging in patients with confirmed prostate cancer. Eur J Nucl Med Mol Imaging 49:763\u2013776","journal-title":"Eur J Nucl Med Mol Imaging"},{"key":"2137_CR23","doi-asserted-by":"publisher","first-page":"2101","DOI":"10.3390\/diagnostics12092101","volume":"12","author":"E Tr\u00e4g\u00e5rdh","year":"2022","unstructured":"Tr\u00e4g\u00e5rdh E, Enqvist O, Ul\u00e9n J et al (2022) Freely Available, Fully Automated AI-Based Analysis of Primary Tumour and Metastases of Prostate Cancer in Whole-Body [F]-PSMA-1007 PET-CT. Diagnostics (Basel) 12:2101","journal-title":"Diagnostics (Basel)"},{"key":"2137_CR24","doi-asserted-by":"crossref","unstructured":"Seifert R, Rasul S, Seitzer K, et al. (2023) A Prognostic Risk Score for Prostate Cancer Based on PSMA PET\u2013derived Organ-specific Tumor Volumes. Radiology 307:e222010-e.","DOI":"10.1148\/radiol.222010"}],"container-title":["La radiologia medica"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11547-025-02137-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11547-025-02137-1","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11547-025-02137-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T21:03:43Z","timestamp":1771967023000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11547-025-02137-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,30]]},"references-count":24,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2026,2]]}},"alternative-id":["2137"],"URL":"https:\/\/doi.org\/10.1007\/s11547-025-02137-1","relation":{},"ISSN":["1826-6983"],"issn-type":[{"value":"1826-6983","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,30]]},"assertion":[{"value":"8 April 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 October 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 October 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Robert Jeraj is the Chief Scientific Officer and a co-founder of AIQ Solutions, a quantitative medical image analysis software company. Roslyn Francis reports institution funding and consulting fees from AIQ Solutions, outside the submitted work.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interests"}},{"value":"Written informed consent was obtained from all participants before inclusion into the study.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to participate"}},{"value":"Ethics approval was obtained from the Sir Charles Gairdner Osborne Park Health Care Group (SCGHPHCG) Human Research Ethics Committee (RGS 0000003734).","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval"}}]}}