{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,20]],"date-time":"2026-10-20T21:29:11Z","timestamp":1792531751686,"version":"4.5.0"},"reference-count":34,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,7,22]],"date-time":"2025-07-22T00:00:00Z","timestamp":1753142400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,7,22]],"date-time":"2025-07-22T00:00:00Z","timestamp":1753142400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Cancer Imaging"],"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:sec>\n            <jats:title>Objectives<\/jats:title>\n            <jats:p>This study aims to assess the predictive capability of PSMA-PET imaging for disease outcomes in primary prostate cancer post-radical prostatectomy. In addition to conventional lesion uptake measures, the evaluation includes the distance of lesion to the prostate to enhance risk stratification and outcome prediction.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Methods<\/jats:title>\n            <jats:p>A cohort of 190 men diagnosed with primary prostate cancer and undergoing prostatectomy were initially screened, resulting in 103 patients meeting the selection criteria. Imaging parameters, including lesion SUVmax, primary metabolic tumor volume (PMTV), maximum distance from the lesion to the prostate (Dmax), and total distances from the lesion to the prostate (Dtotal), were extracted from 68Ga-PSMA-11 PET images. Findings were dichotomized based on primary lesion uptake, the tumor volume size, Dmax distance, and the presence of metastatic disease. Postoperative biochemical recurrence-free survival (BCRFS) was analyzed using Kaplan\u2013Meier survival plots and Log-rank tests. Furthermore, univariate and multivariate Cox regression analyses were performed to evaluate the association of PET parameters with survival outcomes.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>Clinical and histopathological characteristics were summarized, including age, weight, height, metastasis status, baseline PSA, biopsy Gleason score, pt stage, margin status, and lymph node status. After a median follow-up of 20 months, 66 events occurred, with the estimated 3-year BCRFS being 46%. Increased PSMA intensity (SUVmax\u2009&gt;\u200917.06) was associated with less favorable BCRFS (log-rank <jats:italic>p<\/jats:italic>\u2009=\u20090.017). Increased primary metabolic tumor volume (PMTV\u2009&gt;\u200941.59 cm<jats:sup>3<\/jats:sup>) was also linked to less favorable BCRFS (log-rank <jats:italic>p<\/jats:italic>\u2009=\u20090.003). Dmax and Dtotal greater than 9.69\u00a0cm and 11.95\u00a0cm were identified as negative prognostic factors for BCRFS (log-rank <jats:italic>p<\/jats:italic>\u2009&lt;\u20090.001 and <jats:italic>p<\/jats:italic>\u2009=\u20090.002, respectively). Based on PMTV and Dmax, patients were stratified into low-, intermediate-, and high-risk groups, with 3-year BCRFS rates of 57%, 31%, and 8%, respectively. Univariate Cox regression analysis revealed significant associations between BCRFS and factors such as baseline PSA (HR: 1.69, 95% CI 1.02\u20132.79, <jats:italic>p<\/jats:italic>\u2009=\u20090.042), SUVmax (HR: 1.56, 95% CI 1.04\u20131.91, <jats:italic>p<\/jats:italic>\u2009=\u20090.018), PMTV (HR: 2.05, 95% CI 1.26\u20133.34, <jats:italic>p<\/jats:italic>\u2009=\u20090.004), Dmax (HR: 2.24, 95% CI 1.37\u20133.65, <jats:italic>p<\/jats:italic>\u2009=\u20090.001), and Dtotal (HR: 2.11, 95% CI 1.29\u20133.45, <jats:italic>p<\/jats:italic>\u2009=\u20090.003). Multivariable Cox regression analysis identified the best model with PMTV (HR: 2.57, <jats:italic>p<\/jats:italic>\u2009=\u20090.004) and Dmax (HR: 1.98, <jats:italic>p<\/jats:italic>\u2009=\u20090.009) as independent predictors for biochemical recurrence (C-index\u2009=\u20090.68).<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusion<\/jats:title>\n            <jats:p>The lesion distance to prostate was defined and assessed in conjunction with conventional PET parameters to facilitate preoperative risk stratification in primary prostate cancer following radical prostatectomy. The findings contribute to improved outcome prediction and emphasize the potential of PSMA-PET imaging in enhancing management strategies for prostate cancer patients.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Clinical relevance<\/jats:title>\n            <jats:p>There is a critical need for non-invasive biomarkers that can predict treatment outcomes for patients with primary prostate cancer. Our study introduces the concept of using distance metrics, specifically the lesion distance to prostate in baseline PSMA-PET scans, to improve the prediction of biochemical recurrence following prostatectomy. These distance metrics consider the spatial distribution of lesions, offering a novel approach to assessing tumor spread and its implications for patient outcomes.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/s40644-025-00907-8","type":"journal-article","created":{"date-parts":[[2025,7,22]],"date-time":"2025-07-22T08:39:40Z","timestamp":1753173580000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["PSMA-PET-derived distance features as biomarkers for predicting outcomes in primary prostate cancer post-radical prostatectomy"],"prefix":"10.1186","volume":"25","author":[{"given":"Ruohua","family":"Chen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ye","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dong","family":"Liang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianjun","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tao","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,7,22]]},"reference":[{"key":"907_CR1","doi-asserted-by":"publisher","first-page":"1545","DOI":"10.2967\/jnumed.117.191031","volume":"58","author":"SM Schwarzenboeck","year":"2017","unstructured":"Schwarzenboeck SM, Rauscher I, Bluemel C, Fendler WP, Rowe SP, Pomper MG, et al. PSMA ligands for PET imaging of prostate cancer. J Nucl Med. 2017;58:1545\u201352.","journal-title":"J Nucl Med"},{"key":"907_CR2","doi-asserted-by":"crossref","unstructured":"Freedland SJ, Presti JC, Amling CL, Kane CJ, Aronson WJ, Dorey F et al. Time trends in biochemical recurrence after radical prostatectomy: results of the SEARCH database. Urology. 2003;61:736\u201341. Available from: https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0090429502025268","DOI":"10.1016\/S0090-4295(02)02526-8"},{"key":"907_CR3","doi-asserted-by":"crossref","unstructured":"Cao D, Kibel AS, Gao F, Tao Y, Humphrey PA. The Gleason score of tumor at the margin in radical prostatectomy is predictive of biochemical recurrence. Am J Surg Pathol. 2010;34(7):994\u20131001. Available from: https:\/\/journals.lww.com\/ajsp\/fulltext\/2010\/07000\/the_gleason_score_of_tumor_at_the_margin_in.11.aspx","DOI":"10.1097\/PAS.0b013e3181e103bf"},{"key":"907_CR4","doi-asserted-by":"publisher","first-page":"2502","DOI":"10.1007\/s00330-015-4077-5","volume":"26","author":"SY Park","year":"2016","unstructured":"Park SY, Oh YT, Jung DC, Cho NH, Choi YD, Rha KH, et al. Prediction of biochemical recurrence after radical prostatectomy with PI-RADS version 2 in prostate cancers: initial results. Eur Radiol. 2016;26:2502\u20139.","journal-title":"Eur Radiol"},{"key":"907_CR5","doi-asserted-by":"crossref","unstructured":"Luzzago S, Colombo A, Mistretta FA, Alessi S, DiTrapani E, Summers PE et al. Multiparametric MRI-based 5-year risk prediction model for biochemical recurrence of prostate cancer after radical prostatectomy. Radiology. 2023;309:2.","DOI":"10.1148\/radiol.223349"},{"key":"907_CR6","doi-asserted-by":"crossref","unstructured":"Lavall\u00e9e E, Bergeron M, Buteau F-A, Blouin A-C, Duchesnay N, Dujardin T et al. Increased prostate cancer glucose metabolism detected by 18f-fluorodeoxyglucose positron emission tomography\/computed tomography in localised gleason 8\u201310 prostate cancers identifies very high\u2013risk patients for early recurrence and resistance to castration. Eur Urol Focus. 2019;5:998\u20131006. Available from: https:\/\/www.sciencedirect.com\/science\/article\/pii\/S2405456918300865","DOI":"10.1016\/j.euf.2018.03.008"},{"key":"907_CR7","doi-asserted-by":"publisher","first-page":"233","DOI":"10.2967\/jnumed.113.123380","volume":"55","author":"G Giovacchini","year":"2014","unstructured":"Giovacchini G, Picchio M, Garcia-Parra R, Briganti A, Abdollah F, Gianolli L, et al. 11\u00a0C-Choline PET\/CT predicts prostate cancer-specific survival in patients with biochemical failure during androgen-deprivation therapy. J Nucl Med. 2014;55:233\u201341.","journal-title":"J Nucl Med"},{"key":"907_CR8","doi-asserted-by":"crossref","unstructured":"Roberts MJ, Maurer T, Perera M, Eiber M, Hope TA, Ost P et al. Using PSMA imaging for prognostication in localized and advanced prostate cancer. Nat Rev Urol. 2023;20(1):23\u201347.","DOI":"10.1038\/s41585-022-00670-6"},{"key":"907_CR9","doi-asserted-by":"crossref","unstructured":"Karpinski MJ, H\u00fcsing J, Claassen K, M\u00f6ller L, Kaj\u00fcter H, Oesterling F et al. Combining PSMA-PET and PROMISE to re-define disease stage and risk in patients with prostate cancer: a multicentre retrospective study. Lancet Oncol. 2024;25: 1188\u2013201. Available from: https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1470204524003267","DOI":"10.1016\/S1470-2045(24)00326-7"},{"key":"907_CR10","doi-asserted-by":"crossref","unstructured":"Qiu X, Chen M, Yin H, Zhang Q, Li H, Guo S et al. Prediction of biochemical recurrence after radical prostatectomy based on preoperative 68Ga-PSMA-11 PET\/CT. Front Oncol. 2021;11:745530.","DOI":"10.3389\/fonc.2021.745530"},{"key":"907_CR11","doi-asserted-by":"publisher","first-page":"588","DOI":"10.1016\/j.eururo.2023.06.022","volume":"84","author":"L Dja\u00efleb","year":"2023","unstructured":"Dja\u00efleb L, Armstrong WR, Thompson D, Gafita A, Farolfi A, Rajagopal A, et al. Presurgical 68Ga-PSMA-11 positron emission tomography for biochemical recurrence risk assessment: a follow-up analysis of a multicenter prospective phase 3 imaging trial. Eur Urol. 2023;84:588\u201396.","journal-title":"Eur Urol"},{"key":"907_CR12","doi-asserted-by":"publisher","first-page":"3289","DOI":"10.1007\/s00259-022-05756-2","volume":"49","author":"MJ Roberts","year":"2022","unstructured":"Roberts MJ, Morton A, Papa N, Franklin A, Raveenthiran S, Yaxley WJ, et al. Primary tumour PSMA intensity is an independent prognostic biomarker for biochemical recurrence-free survival following radical prostatectomy. Eur J Nucl Med Mol Imaging. 2022;49:3289\u201394.","journal-title":"Eur J Nucl Med Mol Imaging"},{"key":"907_CR13","doi-asserted-by":"crossref","unstructured":"Wang H, Amiel T, W\u00fcrnschimmel C, Langbein T, Steiger K, Rauscher I et al. PSMA-ligand uptake can serve as a novel biomarker in primary prostate cancer to predict outcome after radical prostatectomy. EJNMMI Res. 2021;11(1):76.","DOI":"10.1186\/s13550-021-00818-2"},{"key":"907_CR14","doi-asserted-by":"publisher","first-page":"1822","DOI":"10.2967\/jnumed.122.263897","volume":"63","author":"F Moradi","year":"2022","unstructured":"Moradi F, Duan H, Song H, Davidzon GA, Chung BI, Thong AEC, et al. 68Ga-PSMA-11 PET\/MRI in patients with newly diagnosed intermediate- or high-risk prostate adenocarcinoma: PET findings correlate with outcomes after definitive treatment. J Nucl Med. 2022;63:1822\u20138.","journal-title":"J Nucl Med"},{"key":"907_CR15","doi-asserted-by":"publisher","first-page":"1962","DOI":"10.2967\/jnumed.117.193581","volume":"58","author":"S Schmuck","year":"2017","unstructured":"Schmuck S, Von Klot CA, Henkenberens C, Sohns JM, Christiansen H, Wester HJ, et al. Initial experience with volumetric 68Ga-PSMA I&T PET\/CT for assessment of whole-body tumor burden as a quantitative imaging biomarker in patients with prostate cancer. J Nucl Med. 2017;58:1962\u20138.","journal-title":"J Nucl Med"},{"key":"907_CR16","doi-asserted-by":"publisher","unstructured":"Schmidkonz C, Cordes M, Schmidt D, B\u00e4uerle T, Goetz TI, Beck M et al. 68Ga-PSMA-11 PET\/CT-derived metabolic parameters for determination of whole-body tumor burden and treatment response in prostate cancer. Eur J Nucl Med Mol Imaging. 2018;45:1862\u201372. Available from: https:\/\/doi.org\/10.1007\/s00259-018-4042-z","DOI":"10.1007\/s00259-018-4042-z"},{"key":"907_CR17","doi-asserted-by":"crossref","unstructured":"Kubilay E, Akpinar \u00c7, O\u01e7uz ES, Araz MS, Soydal \u00c7, Baltac\u0131 S et al. Significance of metabolic tumor volume and total lesion uptake measured using Ga-68 labelled prostate-specific membrane antigen PET\/CT in primary staging of prostate cancer. Urologic Oncology: Seminars and Original Investigations. 2022;40:408.e19-408.e25. Available from: https:\/\/www.sciencedirect.com\/science\/article\/pii\/S1078143922002241","DOI":"10.1016\/j.urolonc.2022.06.004"},{"key":"907_CR18","doi-asserted-by":"publisher","unstructured":"Liu C, Liu T, Zhang N, Liu Y, Li N, Du P et al. 68Ga-PSMA-617 PET\/CT: a promising new technique for predicting risk stratification and metastatic risk of prostate cancer patients. Eur J Nucl Med Mol Imaging. 2018;45:1852\u201361. Available from: https:\/\/doi.org\/10.1007\/s00259-018-4037-9","DOI":"10.1007\/s00259-018-4037-9"},{"key":"907_CR19","doi-asserted-by":"crossref","unstructured":"Eiber M, Herrmann K, Calais J, Hadaschik B, Giesel FL, Hartenbach M, et al. Prostate cancer molecular imaging standardized evaluation (PROMISE): proposed MiTNM classification for the interpretation of PSMA-ligand PET\/CT. J Nucl Med. 2018;59:469\u201378.","DOI":"10.2967\/jnumed.117.198119"},{"key":"907_CR20","doi-asserted-by":"crossref","unstructured":"Eder M, Neels O, M\u00fcller M, Bauder-W\u00fcst U, Remde Y, Sch\u00e4fer M, et al. Novel preclinical and radiopharmaceutical aspects of [68Ga]Ga-PSMA-HBED-CC: a new PET tracer for imaging of prostate cancer. Pharmaceuticals. 2014;7:779\u201396.","DOI":"10.3390\/ph7070779"},{"key":"907_CR21","doi-asserted-by":"publisher","unstructured":"Wasserthal J, Breit H-C, Meyer MT, Pradella M, Hinck D, Sauter AW et al. TotalSegmentator: robust segmentation of 104 anatomic structures in CT images. Radiol Artif Intell. 2023;5:e230024. Available from: https:\/\/doi.org\/10.1148\/ryai.230024","DOI":"10.1148\/ryai.230024"},{"key":"907_CR22","doi-asserted-by":"crossref","unstructured":"Shore ND, Moul JW, Pienta KJ, Czernin J, King MT, Freedland SJ. Biochemical recurrence in patients with prostate cancer after primary definitive therapy: treatment based on risk stratification. Prostate Cancer Prostatic Dis. Springer Nature; 2024. pp. 192\u2013201.","DOI":"10.1038\/s41391-023-00712-z"},{"key":"907_CR23","doi-asserted-by":"crossref","unstructured":"Van den Broeck T, van den Bergh RCN, Arfi N, Gross T, Moris L, Briers E, et al. Prognostic value of biochemical recurrence following treatment with curative intent for prostate cancer: a systematic review. Eur Urol. Elsevier B.V.; 2019. pp. 967\u201387.","DOI":"10.1016\/j.eururo.2018.10.011"},{"key":"907_CR24","doi-asserted-by":"crossref","unstructured":"Falkenbach F, Schmalhofer ML, Tian Z, Mazzucato G, Karakiewicz PI, Graefen M et al. Size and SUVmax define the contribution of nodal metastases to PSA in oligorecurrent prostate cancer. Prostate. 2024;85(1):105\u2013111.","DOI":"10.1002\/pros.24806"},{"key":"907_CR25","doi-asserted-by":"crossref","unstructured":"Zapatero A, Conde Moreno AJ, Barrado Los Arcos M, Aldave D. Node oligorecurrence in prostate cancer: a challenge. Cancers (Basel). Multidisciplinary Digital Publishing Institute (MDPI); 2023.","DOI":"10.20944\/preprints202306.1421.v1"},{"key":"907_CR26","doi-asserted-by":"publisher","first-page":"904","DOI":"10.2967\/jnumed.123.267014","volume":"65","author":"M Swiha","year":"2024","unstructured":"Swiha M, Papa N, Sabahi Z, Ayati N, John N, Pathmanandavel S, et al. Development of a visually calculated SUVmean (HIT score) on screening PSMA PET\/CT to predict treatment response to 177Lu-PSMA therapy: comparison with quantitative SUVmean and patient outcomes. J Nucl Med. 2024;65:904\u20138.","journal-title":"J Nucl Med"},{"key":"907_CR27","doi-asserted-by":"publisher","first-page":"404","DOI":"10.1016\/j.annonc.2020.11.019","volume":"32","author":"AS Cottereau","year":"2021","unstructured":"Cottereau AS, Meignan M, Nioche C, Capobianco N, Clerc J, Chartier L, et al. Risk stratification in diffuse large B-cell lymphoma using lesion dissemination and metabolic tumor burden calculated from baseline PET\/CT\u2020. Ann Oncol. 2021;32:404\u201311.","journal-title":"Ann Oncol"},{"key":"907_CR28","doi-asserted-by":"publisher","first-page":"40","DOI":"10.2967\/jnumed.119.229450","volume":"61","author":"AS Cottereau","year":"2020","unstructured":"Cottereau AS, Nioche C, Dirand AS, Clerc J, Morschhauser F, Casasnovas O, et al. 18F-FDG PET dissemination features in diffuse large B-cell lymphoma are predictive of outcome. J Nucl Med. 2020;61:40\u20135.","journal-title":"J Nucl Med"},{"key":"907_CR29","doi-asserted-by":"crossref","unstructured":"Albano D, Treglia G, Dondi F, Calabr\u00f2 A, Rizzo A, Annunziata S, et al. 18F-FDG PET\/CT maximum tumor dissemination (Dmax) in lymphoma: a new prognostic factor? Cancers (Basel). Multidisciplinary Digital Publishing Institute (MDPI); 2023;15(9):2494.","DOI":"10.3390\/cancers15092494"},{"key":"907_CR30","doi-asserted-by":"crossref","unstructured":"Zhou Y, Zhu Y, Chen Z, Li J, Sang S, Deng S. Radiomic features of 18F-FDG PET in Hodgkin lymphoma are predictive of outcomes. Contrast Media Mol Imaging. 2021;2021:6347404.","DOI":"10.1155\/2021\/6347404"},{"key":"907_CR31","doi-asserted-by":"publisher","first-page":"645","DOI":"10.1002\/hon.3025","volume":"40","author":"R Durmo","year":"2022","unstructured":"Durmo R, Donati B, Rebaud L, Cottereau AS, Ruffini A, Nizzoli ME, et al. Prognostic value of lesion dissemination in doxorubicin, bleomycin, vinblastine, and dacarbazine-treated, interimPET-negative classical hodgkin lymphoma patients: a radio-genomic study. Hematol Oncol. 2022;40:645\u201357.","journal-title":"Hematol Oncol"},{"key":"907_CR32","doi-asserted-by":"publisher","first-page":"932","DOI":"10.1007\/s00259-021-05480-3","volume":"49","author":"JJ Eertink","year":"2022","unstructured":"Eertink JJ, van de Brug T, Wiegers SE, Zwezerijnen GJC, Pfaehler EAG, Lugtenburg PJ, et al. 18F-FDG PET baseline radiomics features improve the prediction of treatment outcome in diffuse large B-cell lymphoma. Eur J Nucl Med Mol Imaging. 2022;49:932\u201342.","journal-title":"Eur J Nucl Med Mol Imaging"},{"key":"907_CR33","doi-asserted-by":"publisher","first-page":"310","DOI":"10.1007\/s12149-021-01705-5","volume":"36","author":"A Aksu","year":"2022","unstructured":"Aksu A, Vural Topuz \u00d6, Y\u0131lmaz G, \u00c7apa Kaya G, Y\u0131lmaz B. Dual time point imaging of staging PSMA PET\/CT quantification; spread and radiomic analyses. Ann Nucl Med. 2022;36:310\u20138.","journal-title":"Ann Nucl Med"},{"key":"907_CR34","doi-asserted-by":"publisher","first-page":"468","DOI":"10.1097\/MNM.0000000000001539","volume":"43","author":"A Aksu","year":"2022","unstructured":"Aksu A, Vural Topuz \u00d6, Yilmaz B, Karahan \u015een NP, Acar E, \u00c7apa Kaya G. Prediction of early biochemical response after 177Lu-PSMA radioligand therapy with 68Ga-PSMA PET, a different perspective with quantitative parameters. Nucl Med Commun. 2022;43:468\u201374.","journal-title":"Nucl Med Commun"}],"container-title":["Cancer Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s40644-025-00907-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s40644-025-00907-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s40644-025-00907-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,7]],"date-time":"2025-09-07T17:37:06Z","timestamp":1757266626000},"score":1,"resource":{"primary":{"URL":"https:\/\/cancerimagingjournal.biomedcentral.com\/articles\/10.1186\/s40644-025-00907-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,22]]},"references-count":34,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["907"],"URL":"https:\/\/doi.org\/10.1186\/s40644-025-00907-8","relation":{},"ISSN":["1470-7330"],"issn-type":[{"value":"1470-7330","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,7,22]]},"assertion":[{"value":"5 December 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 July 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 July 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":"The experimental investigation with human subjects reported in the manuscript was performed with informed consent and following the guidelines for human experimental investigation required by the institutions. The study was approved by the Ethics Committee of Shanghai Renji Hospital (IRB 2018\u2009\u2212\u2009104).","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"The content of the manuscript has not been published or submitted for publication elsewhere. All authors have approved the manuscript for submission.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"93"}}