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Articles published in
Cancer Imaging
    February 2026
  1. POROES F, Nobile A, Widmer L, Vidal J, et al
    Maximal radial distance for predicting extraprostatic extension of prostate cancer: a histopathological-radiological study.
    Cancer Imaging. 2026 Feb 21. doi: 10.1186/s40644-026-01011.
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    January 2026
  2. LIN LP, Cheng XW, Chen J, Li SY, et al
    Prognostic features of biochemical recurrence of prostate cancer following radical prostatectomy based on diffusion kurtosis imaging.
    Cancer Imaging. 2026 Jan 28. doi: 10.1186/s40644-026-00997.
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  3. LOWRY NC, Breto AL, Wallaengen V, Algohary A, et al
    MRI-based patient selection for active surveillance in prostate cancer using U-Found: a generalized deep learning model.
    Cancer Imaging. 2026 Jan 19. doi: 10.1186/s40644-026-00988.
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    December 2025
  4. BERG EK, Kunte SC, Zahner J, Holzgreve A, et al
    PSMA expression assessed by [(18)F]PSMA-1007 PET/CT imaging in metastatic hormone-sensitive prostate cancer patients treated with apalutamide.
    Cancer Imaging. 2025;25:136.
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    September 2025
  5. MIN K, Lin Q, Qiu D
    Precision medicine in prostate cancer: individualized treatment through radiomics, genomics, and biomarkers.
    Cancer Imaging. 2025;25:116.
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    August 2025
  6. A GLEMSER P, Netzer N, H Ziener C, Wilhelm M, et al
    Improving risk stratification of PI-RADS 3 + 1 lesions of the peripheral zone: expert lexicon of terms, multi-reader performance and contribution of artificial intelligence.
    Cancer Imaging. 2025;25:102.
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  7. YAO F, Lin H, Xue YN, Zhuang YD, et al
    Multimodal imaging deep learning model for predicting extraprostatic extension in prostate cancer using MpMRI and 18 F-PSMA-PET/CT.
    Cancer Imaging. 2025;25:103.
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    July 2025
  8. CHEN R, Li Y, Liang D, Liu J, et al
    PSMA-PET-derived distance features as biomarkers for predicting outcomes in primary prostate cancer post-radical prostatectomy.
    Cancer Imaging. 2025;25:93.
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  9. ZAMANIAN A, Rousseau E, Buteau FA, Arsenault F, et al
    The tumour sink effect on (68)Ga-PSMA-PET/CT in metastatic castration-resistant prostate cancer and its implications for PSMA-RPT: a sub-analysis of the 3TMPO study.
    Cancer Imaging. 2025;25:91.
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  10. KORN SM, Qian Z, Zurl H, Hansen N, et al
    Geographic variability in contemporary utilization of PET imaging for prostate cancer: a medicare claims cohort study.
    Cancer Imaging. 2025;25:86.
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  11. YANG L, Jin P, Wang X, Li Z, et al
    Development and validation of a novel clinical-radiological-pathological scoring system for preoperative prediction of extraprostatic extension in prostate cancer: a multicenter retrospective study.
    Cancer Imaging. 2025;25:83.
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    June 2025
  12. BIAN L, Liu F, Peng Y, Liu X, et al
    Using radiomics model for predicting extraprostatic extension with PSMA PET/CT studies: a comparative study with the Mehralivand grading system.
    Cancer Imaging. 2025;25:77.
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    April 2025
  13. MOAVENZADEH SR, Chan DY, Adams ES, Deivasigamani S, et al
    Evaluation of 3D ARFI imaging of prostate cancer: diagnostic reliability and concordance with MpMRI.
    Cancer Imaging. 2025;25:55.
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  14. ZEDAN AH, Gade JS, Zieger KEA, Poulsen MH, et al
    Cabazitaxel-induced ureteritis in metastatic castration-resistant prostate cancer patients: a single center case series 2014-2024.
    Cancer Imaging. 2025;25:54.
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    March 2025
  15. SUN Z, Wu P, Zhao T, Gao G, et al
    Deep learning-based fully automated detection and segmentation of pelvic lymph nodes on diffusion-weighted images for prostate cancer: a multicenter study.
    Cancer Imaging. 2025;25:37.
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  16. POROES F, Karampa P, Sartoretti T, Najberg H, et al
    Additional findings in prostate MRI.
    Cancer Imaging. 2025;25:29.
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    January 2025
  17. HUANG X, Ye H, Hu Y, Lei Y, et al
    Ultrasound super-resolution imaging for non-invasive assessment of microvessel in prostate lesion.
    Cancer Imaging. 2025;25:1.
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    October 2024
  18. BURGARD C, Rosar F, Larsen E, Khreish F, et al
    Outstanding increase in tumor-to-background ratio over time allows tumor localization by [(89)Zr]Zr-PSMA-617 PET/CT in early biochemical recurrence of prostate cancer.
    Cancer Imaging. 2024;24:132.
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    September 2024
  19. VENTURA D, Rassek P, Schindler P, Akkurt BH, et al
    Early treatment response assessment with [(177)Lu]PSMA whole-body-scintigraphy compared to interim PSMA-PET.
    Cancer Imaging. 2024;24:126.
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    August 2024
  20. HARSINI S, Martineau P, Plaha S, Saprunoff H, et al
    Prognostic significance of a negative PSMA PET/CT in biochemical recurrence of prostate cancer.
    Cancer Imaging. 2024;24:117.
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  21. XU L, Peng Q, Zhang G, Zhang D, et al
    Development of preoperative nomograms to predict the risk of overall and multifocal positive surgical margin after radical prostatectomy.
    Cancer Imaging. 2024;24:104.
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    July 2024
  22. FURMAN B, Falick Michaeli T, Den R, Ben Haim S, et al
    Pelvic lymph node mapping in prostate cancer: examining the impact of PSMA PET/CT on radiotherapy decision-making in patients with node-positive disease.
    Cancer Imaging. 2024;24:96.
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  23. KALLIS K, Conlin CC, Zhong AY, Hussain TS, et al
    Comparison of synthesized and acquired high b-value diffusion-weighted MRI for detection of prostate cancer.
    Cancer Imaging. 2024;24:89.
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  24. YANG J, Xiao L, Zhou M, Li Y, et al
    [(68)Ga]Ga?PSMA?617 PET-based radiomics model to identify candidates for active surveillance amongst patients with GGG 1-2 prostate cancer at biopsy.
    Cancer Imaging. 2024;24:86.
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  25. GROSS M, Eisenhuber E, Assinger P, Schima R, et al
    MRI-guided in-bore biopsy of the prostate - defining the optimal number of cores needed.
    Cancer Imaging. 2024;24:81.
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    May 2024
  26. AYATI N, McIntosh L, Buteau J, Alipour R, et al
    Comparison of quantitative whole body PET parameters on [(68)Ga]Ga-PSMA-11 PET/CT using ordered Subset Expectation Maximization (OSEM) vs. bayesian penalized likelihood (BPL) reconstruction algorithms in men with metastatic castration-resistant prosta
    Cancer Imaging. 2024;24:57.
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    April 2024
  27. KOLADE OU, Brink A, Ayeni AO, More S, et al
    Optimizing PSMA scintigraphy for resource limited settings - a retrospective comparative study.
    Cancer Imaging. 2024;24:46.
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    February 2024
  28. YAZDANI E, Karamzadeh-Ziarati N, Cheshmi SS, Sadeghi M, et al
    Automated segmentation of lesions and organs at risk on [(68)Ga]Ga-PSMA-11 PET/CT images using self-supervised learning with Swin UNETR.
    Cancer Imaging. 2024;24:30.
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  29. ROSAR F, Burgard C, Larsen E, Khreish F, et al
    [(89)Zr]Zr-PSMA-617 PET/CT characterization of indeterminate [(68)Ga]Ga-PSMA-11 PET/CT findings in patients with biochemical recurrence of prostate cancer: lesion-based analysis.
    Cancer Imaging. 2024;24:27.
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  30. GUERRA A, Orton MR, Wang H, Konidari M, et al
    Clinical application of machine learning models in patients with prostate cancer before prostatectomy.
    Cancer Imaging. 2024;24:24.
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  31. HU C, Qiao X, Hu C, Cao C, et al
    The practical clinical role of machine learning models with different algorithms in predicting prostate cancer local recurrence after radical prostatectomy.
    Cancer Imaging. 2024;24:23.
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    January 2024
  32. MA Y, Gao F
    Advances of radiolabeled GRPR ligands for PET/CT imaging of cancers.
    Cancer Imaging. 2024;24:19.
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    December 2023
  33. DONNERS R, Figueiredo I, Westaby D, Koh DM, et al
    Multiparametric bone MRI targeting aides lesion selection for CT-guided sclerotic bone biopsies in metastatic castrate resistant prostate cancer.
    Cancer Imaging. 2023;23:121.
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    November 2023
  34. PENG Q, Xu L, Zhang G, Zhang D, et al
    Effect of preoperative PI-RADS assessment on pathological outcomes in patients who underwent radical prostatectomy.
    Cancer Imaging. 2023;23:113.
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  35. LUO L, Zheng A, Chang R, Li Y, et al
    Evaluating the value of (18)F-PSMA-1007 PET/CT in the detection and identification of prostate cancer using histopathology as the standard.
    Cancer Imaging. 2023;23:108.
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    September 2023
  36. HU B, Zhang H, Zhang Y, Jin Y, et al
    A nomogram based on biparametric magnetic resonance imaging for detection of clinically significant prostate cancer in biopsy-naive patients.
    Cancer Imaging. 2023;23:82.
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  37. YANG J, Li J, Xiao L, Zhou M, et al
    (68)Ga-PSMA PET/CT-based multivariate model for highly accurate and noninvasive diagnosis of clinically significant prostate cancer in the PSA gray zone.
    Cancer Imaging. 2023;23:81.
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