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A PSMA PET/CT-based risk model for prediction of concordance between targeted biopsy and combined biopsy in detecting prostate cancer

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World Journal of Urology Aims and scope Submit manuscript

Abstract

Purpose

This study is to investigate the diagnostic value of 68Ga-PSMA-11 in improving the concordance between mpMRI-TB and combined biopsy (CB) in detecting PCa.

Methods

115 consecutive men with 68Ga-PSMA-11 PET/CT prior to prostate biopsy were included for analysis. PSMA intensity, quantified as maximum standard uptake value (SUVmax), minimum apparent diffusion coefficient (ADCmin) and other clinical characteristics were evaluated relative to biopsy concordance using univariate and multivariate logistic regression analyses. A prediction model was developed based on the identified parameters, and a dynamic online diagnostic nomogram was constructed, with its discrimination evaluated through the area under the ROC curve (AUC) and consistency assessed using calibration plots. To assess its clinical applicability, a decision curve analysis (DCA) was performed, while internal validation was conducted using bootstrapping methods.

Results

Concordance between mpMRI-TB and CB occurred in 76.5% (88/115) of the patients. Multivariate logistic regression analyses performed that SUVmax (OR= 0.952; 95% CI 0.917–0.988; P= 0.010) and ADCmin (OR= 1.006; 95% CI 1.003–1.010; P= 0.001) were independent risk factors for biopsy concordance. The developed model showed a sensitivity, specificity, accuracy and AUC of 0.67, 0.78, 0.81 and 0.78 in the full sample. The calibration curve demonstrated that the nomogram’s predicted outcomes closely resembled the ideal curve, indicating consistency between predicted and actual outcomes. Furthermore, the decision curve analysis (DCA) highlighted the clinical net benefit achievable across various risk thresholds. These findings were reinforced by internal validation.

Conclusions

The developed prediction model based on SUVmax and ADCmin showed practical value in guiding the optimization of prostate biopsy pattern. Lower SUVmax and Higher ADCmin values are associated with greater confidence in implementing mono-TB and safely avoiding SB, effectively balancing benefits and risks.

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Data availability

The data of PSMA PET/CT were generated at the Department of Nuclear Medicine, Nanjing First Hospital, Nanjing Medical University, and other raw data were generated at the Department of Urology, Affiliated Drum Tower Hospital, Medical School of Nanjing University. Derived data supporting the findings of this study are available on request.

References

  1. Siegel RL, Miller KD, Fuchs HE, Jemal A (2022) Cancer statistics, 2022. CA A Cancer J Clin 72(1):7–33

    Article  Google Scholar 

  2. Andras I, Crisan D, Cata E, Tamas-Szora A, Caraiani C, Coman RT, Bungardean C, Mirescu C, Coman I, Crisan N (2019) MRI-TRUS fusion guided prostate biopsy - initial experience and assessment of the role of contralateral lobe systematic biopsy. Med Ultrason 21(1):37–44

    Article  PubMed  Google Scholar 

  3. Immerzeel J, Israël B, Bomers J, Schoots IG, van Basten JP, Kurth KH, de Reijke T, Sedelaar M, Debruyne F, Barentsz J (2022) Multiparametric magnetic resonance imaging for the detection of clinically significant prostate cancer: what urologists need to know. Part 4: transperineal magnetic resonance-ultrasound fusion guided biopsy using local anesthesia. Eur Urol 81(1):110–117

    Article  CAS  PubMed  Google Scholar 

  4. Schoots IG, Padhani AR, Rouvière O, Barentsz JO, Richenberg J (2020) Analysis of magnetic resonance imaging-directed biopsy strategies for changing the paradigm of prostate cancer diagnosis. Eur Urol Oncol 3(1):32–41

    Article  PubMed  Google Scholar 

  5. Eklund M, Jäderling F, Discacciati A, Bergman M, Annerstedt M, Aly M, Glaessgen A, Carlsson S, Grönberg H, Nordström T (2021) MRI-targeted or standard biopsy in prostate cancer screening. N Engl J Med 385(10):908–920

    Article  PubMed  Google Scholar 

  6. Alkema NG, Hoogeveen SFJS, Cauberg ECC, Witte LPW, van’t Veer-Ten M, de Boer E, Hoogland MAM, Blanker MH, Boomsma MF, Steffens MG (2022) Magnetic resonance imaging-targeted prostate biopsy compared with systematic prostate biopsy in biopsy-naïve patients with suspected prostate cancer. Eur Urol Open Sci 44:125–130

    Article  PubMed  PubMed Central  Google Scholar 

  7. Hofman MS, Lawrentschuk N, Francis RJ, Tang C, Vela I, Thomas P, Rutherford N, Martin JM, Frydenberg M, Shakher R et al (2020) Prostate-specific membrane antigen PET-CT in patients with high-risk prostate cancer before curative-intent surgery or radiotherapy (proPSMA): a prospective, randomised, multicentre study. Lancet 395(10231):1208–1216

    Article  CAS  PubMed  Google Scholar 

  8. Lopci E, Piccardo A, Lazzeri M (2019) Prostate cancer imaging and therapeutic alternatives with highly specific molecular ‘probes.’ BJU Int 124(2):188–189

    Article  PubMed  Google Scholar 

  9. Fendler WP, Calais J, Eiber M, Flavell RR, Mishoe A, Feng FY, Nguyen HG, Reiter RE, Rettig MB, Okamoto S et al (2019) Assessment of 68Ga-PSMA-11 PET accuracy in localizing recurrent prostate cancer: a prospective single-arm clinical trial. JAMA Oncol 5(6):856–863

    Article  PubMed  PubMed Central  Google Scholar 

  10. Lopci E, Lughezzani G, Castello A, Saita A, Colombo P, Hurle R, Peschechera R, Benetti A, Zandegiacomo S, Pasini L et al (2021) Prospective evaluation of (68)ga-labeled prostate-specific membrane antigen ligand positron emission tomography/computed tomography in primary prostate cancer diagnosis. Eur Urol Focus 7(4):764–771

    Article  PubMed  Google Scholar 

  11. Zamboglou C, Carles M, Fechter T, Kiefer S, Reichel K, Fassbender TF, Bronsert P, Koeber G, Schilling O, Ruf J et al (2019) Radiomic features from PSMA PET for non-invasive intraprostatic tumor discrimination and characterization in patients with intermediate- and high-risk prostate cancer - a comparison study with histology reference. Theranostics 9(9):2595–2605

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Cysouw MCF, Jansen BHE, van de Brug T, Oprea-Lager DE, Pfaehler E, de Vries BM, van Moorselaar RJA, Hoekstra OS, Vis AN, Boellaard R (2021) Machine learning-based analysis of [(18)F]DCFPyL PET radiomics for risk stratification in primary prostate cancer. Eur J Nucl Med Mol Imaging 48(2):340–349

    Article  CAS  PubMed  Google Scholar 

  13. Yin H, Chen M, Qiu X, Qiu L, Gao J, Li D, Fu Y, Huang H, Guo S, Zhang Q et al (2021) Can (68)Ga-PSMA-11 PET/CT predict pathological upgrading of prostate cancer from MRI-targeted biopsy to radical prostatectomy? Eur J Nucl Med Mol Imaging 48(11):3693–3701

    Article  CAS  PubMed  Google Scholar 

  14. Zhang Q, Zang S, Zhang C, Fu Y, Lv X, Zhang Q, Deng Y, Zhang C, Luo R, Zhao X et al (2017) Comparison of (68)Ga-PSMA-11 PET-CT with mpMRI for preoperative lymph node staging in patients with intermediate to high-risk prostate cancer. J Transl Med 15(1):230

    Article  PubMed  PubMed Central  Google Scholar 

  15. Fanti S, Goffin K, Hadaschik BA, Herrmann K, Maurer T, MacLennan S, Oprea-Lager DE, Oyen WJ, Rouvière O, Mottet N et al (2021) Consensus statements on PSMA PET/CT response assessment criteria in prostate cancer. Eur J Nucl Med Mol Imaging 48(2):469–476

    Article  PubMed  Google Scholar 

  16. Marra G, Zhuang J, Beltrami M, Calleris G, Zhao X, Marquis A, Kan Y, Oderda M, Huang H, Faletti R et al (2021) Transperineal freehand multiparametric MRI fusion targeted biopsies under local anaesthesia for prostate cancer diagnosis: a multicentre prospective study of 1014 cases. BJU Int 127(1):122–130

    Article  CAS  PubMed  Google Scholar 

  17. Epstein JI, Egevad L, Amin MB, Delahunt B, Srigley JR, Humphrey PA (2016) The 2014 international society of urological pathology (ISUP) consensus conference on gleason grading of prostatic carcinoma: definition of grading patterns and proposal for a new grading system. Am J Surg Pathol 40(2):244–252

    Article  PubMed  Google Scholar 

  18. Raman AG, Sarma KV, Raman SS, Priester AM, Mirak SA, Riskin-Jones HH, Dhinagar N, Speier W, Felker E, Sisk AE et al (2021) Optimizing spatial biopsy sampling for the detection of prostate cancer. J Urol 206(3):595–603

    Article  PubMed  PubMed Central  Google Scholar 

  19. Demirci E, Kabasakal L, Şahin OE, Akgün E, Gültekin MH, Doğanca T, Tuna MB, Öbek C, Kiliç M, Esen T et al (2019) Can SUVmax values of Ga-68-PSMA PET/CT scan predict the clinically significant prostate cancer? Nucl Med Commun 40(1):86–91

    Article  PubMed  Google Scholar 

  20. Chen M, Qiu X, Zhang Q, Zhang C, Zhou YH, Zhao X, Fu Y, Wang F, Guo H (2022) PSMA uptake on [68Ga]-PSMA-11-PET/CT positively correlates with prostate cancer aggressiveness. Q J Nucl Med Mol Imaging 66(1):67–73

    Article  PubMed  Google Scholar 

  21. Le Bihan D (2013) Apparent diffusion coefficient and beyond: what diffusion MR imaging can tell us about tissue structure. Radiology 268(2):318–322

    Article  PubMed  Google Scholar 

  22. Peng Y, Jiang Y, Yang C, Brown JB, Antic T, Sethi I, Schmid-Tannwald C, Giger ML, Eggener SE, Oto A (2013) Quantitative analysis of multiparametric prostate MR images: differentiation between prostate cancer and normal tissue and correlation with Gleason score–a computer-aided diagnosis development study. Radiology 267(3):787–796

    Article  PubMed  Google Scholar 

  23. Donati OF, Mazaheri Y, Afaq A, Vargas HA, Zheng J, Moskowitz CS, Hricak H, Akin O (2014) Prostate cancer aggressiveness: assessment with whole-lesion histogram analysis of the apparent diffusion coefficient. Radiology 271(1):143–152

    Article  PubMed  Google Scholar 

  24. Hagens MJ, Fernandez Salamanca M, Padhani AR, van Leeuwen PJ, van der Poel HG, Schoots IG (2022) Diagnostic performance of a magnetic resonance imaging-directed targeted plus regional biopsy approach in prostate cancer diagnosis: a systematic review and meta-analysis. Eur Urol Open Sci 40:95–103

    Article  PubMed  PubMed Central  Google Scholar 

  25. Mazzone E, Stabile A, Pellegrino F, Basile G, Cignoli D, Cirulli GO, Sorce G, Barletta F, Scuderi S, Bravi CA et al (2021) Positive predictive value of prostate imaging reporting and data system version 2 for the detection of clinically significant prostate cancer: a systematic review and meta-analysis. Eur Urol Oncol 4(5):697–713

    Article  PubMed  Google Scholar 

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Funding

Partial financial support was received from the Sino-German Mobility Programme (M-0670), the Natural Science Foundation of Jiangsu Province (BE2020622)

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Authors and Affiliations

Authors

Contributions

Chaoli An: Project development, Data management, Manuscript writing. Yao Fu: Administrative, technical and material support. Hongqian Guo: Project development, Manuscript editing. Beibei Liu: Data management. Xuefeng Qiu: Project development, Manuscript editing. Xiang Song: Data management. Jiaxin Shu: Data analysis. Feng Wang: Administrative, technical and material support. Yu Yang: Data analysis. Xiaozhi Zhao: Manuscript editing

Corresponding authors

Correspondence to Feng Wang, Xiaozhi Zhao or Hongqian Guo.

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Conflict of interest

The authors have no competing interests to declare that are relevant to the content of this article

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. This study was approved by the institutional review board of Nanjing Drum Tower Hospital, Medical School of Nanjing University (approval 2020-173-02).

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Informed consent was obtained from all individual participants included in the study.

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An, C., Qiu, X., Liu, B. et al. A PSMA PET/CT-based risk model for prediction of concordance between targeted biopsy and combined biopsy in detecting prostate cancer. World J Urol 42, 285 (2024). https://doi.org/10.1007/s00345-024-04947-w

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