Dual-Tracer PET-MRI-Derived Imaging Biomarkers for Prediction of Clinically Significant Prostate Cancer
Purpose: To investigate if imaging biomarkers derived from 3-Tesla dual-tracer [(18)F]fluoromethylcholine (FMC) and [<sup>68</sup>Ga]Ga-PSMA<sup>HBED-CC</sup> conjugate 11 (PSMA)-positron emission tomography can adequately predict clinically significant prostate cancer (csPC)...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-01-01
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| Series: | Current Oncology |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1718-7729/30/2/129 |
| _version_ | 1827757900120981504 |
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| author | Bernhard Grubmüller Nicolai A. Huebner Sazan Rasul Paola Clauser Nina Pötsch Karl Hermann Grubmüller Marcus Hacker Sabrina Hartenbach Shahrokh F. Shariat Markus Hartenbach Pascal Baltzer |
| author_facet | Bernhard Grubmüller Nicolai A. Huebner Sazan Rasul Paola Clauser Nina Pötsch Karl Hermann Grubmüller Marcus Hacker Sabrina Hartenbach Shahrokh F. Shariat Markus Hartenbach Pascal Baltzer |
| author_sort | Bernhard Grubmüller |
| collection | DOAJ |
| description | Purpose: To investigate if imaging biomarkers derived from 3-Tesla dual-tracer [(18)F]fluoromethylcholine (FMC) and [<sup>68</sup>Ga]Ga-PSMA<sup>HBED-CC</sup> conjugate 11 (PSMA)-positron emission tomography can adequately predict clinically significant prostate cancer (csPC). Methods: We assessed 77 biopsy-proven PC patients who underwent 3T dual-tracer PET/mpMRI followed by radical prostatectomy (RP) between 2014 and 2017. We performed a retrospective lesion-based analysis of all cancer foci and compared it to whole-mount histopathology of the RP specimen. The primary aim was to investigate the pretherapeutic role of the imaging biomarkers FMC- and PSMA-maximum standardized uptake values (SUVmax) for the prediction of csPC and to compare it to the mpMRI-methods and PI-RADS score. Results: Overall, we identified 104 cancer foci, 69 were clinically significant (66.3%) and 35 were clinically insignificant (33.7%). We found that the combined FMC+PSMA SUVmax were the only significant parameters (<i>p</i> < 0.001 and <i>p</i> = 0.049) for the prediction of csPC. ROC analysis showed an AUC for the prediction of csPC of 0.695 for PI-RADS scoring (95% CI 0.591 to 0.786), 0.792 for FMC SUVmax (95% CI 0.696 to 0.869), 0.852 for FMC+PSMA SUVmax (95% CI 0.764 to 0.917), and 0.852 for the multivariable CHAID model (95% CI 0.763 to 0.916). Comparing the AUCs, we found that FMC+PSMA SUVmax and the multivariable model were significantly more accurate for the prediction of csPC compared to PI-RADS scoring (<i>p</i> = 0.0123, <i>p</i> = 0.0253, respectively). Conclusions: Combined FMC+PSMA SUVmax seems to be a reliable parameter for the prediction of csPC and might overcome the limitations of PI-RADS scoring. Further prospective studies are necessary to confirm these promising preliminary results. |
| first_indexed | 2024-03-11T08:57:57Z |
| format | Article |
| id | doaj.art-76446ed65a67478791b5828ff707b377 |
| institution | Directory Open Access Journal |
| issn | 1198-0052 1718-7729 |
| language | English |
| last_indexed | 2024-03-11T08:57:57Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Current Oncology |
| spelling | doaj.art-76446ed65a67478791b5828ff707b3772023-11-16T19:57:42ZengMDPI AGCurrent Oncology1198-00521718-77292023-01-013021683169110.3390/curroncol30020129Dual-Tracer PET-MRI-Derived Imaging Biomarkers for Prediction of Clinically Significant Prostate CancerBernhard Grubmüller0Nicolai A. Huebner1Sazan Rasul2Paola Clauser3Nina Pötsch4Karl Hermann Grubmüller5Marcus Hacker6Sabrina Hartenbach7Shahrokh F. Shariat8Markus Hartenbach9Pascal Baltzer10Department of Urology, Medical University of Vienna, 1090 Vienna, AustriaDepartment of Urology, Medical University of Vienna, 1090 Vienna, AustriaDepartment of Biomedical Imaging and Image Guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, 1090 Vienna, AustriaDepartment of Biomedical Imaging and Image Guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna, 1090 Vienna, AustriaDepartment of Biomedical Imaging and Image Guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna, 1090 Vienna, AustriaDepartment of Urology and Andrology, University Hospital Krems, 3500 Krems, AustriaDepartment of Biomedical Imaging and Image Guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, 1090 Vienna, AustriaHistoConsultingHartenbach, 89081 Ulm, GermanyDepartment of Urology, Medical University of Vienna, 1090 Vienna, AustriaDepartment of Biomedical Imaging and Image Guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, 1090 Vienna, AustriaDepartment of Biomedical Imaging and Image Guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna, 1090 Vienna, AustriaPurpose: To investigate if imaging biomarkers derived from 3-Tesla dual-tracer [(18)F]fluoromethylcholine (FMC) and [<sup>68</sup>Ga]Ga-PSMA<sup>HBED-CC</sup> conjugate 11 (PSMA)-positron emission tomography can adequately predict clinically significant prostate cancer (csPC). Methods: We assessed 77 biopsy-proven PC patients who underwent 3T dual-tracer PET/mpMRI followed by radical prostatectomy (RP) between 2014 and 2017. We performed a retrospective lesion-based analysis of all cancer foci and compared it to whole-mount histopathology of the RP specimen. The primary aim was to investigate the pretherapeutic role of the imaging biomarkers FMC- and PSMA-maximum standardized uptake values (SUVmax) for the prediction of csPC and to compare it to the mpMRI-methods and PI-RADS score. Results: Overall, we identified 104 cancer foci, 69 were clinically significant (66.3%) and 35 were clinically insignificant (33.7%). We found that the combined FMC+PSMA SUVmax were the only significant parameters (<i>p</i> < 0.001 and <i>p</i> = 0.049) for the prediction of csPC. ROC analysis showed an AUC for the prediction of csPC of 0.695 for PI-RADS scoring (95% CI 0.591 to 0.786), 0.792 for FMC SUVmax (95% CI 0.696 to 0.869), 0.852 for FMC+PSMA SUVmax (95% CI 0.764 to 0.917), and 0.852 for the multivariable CHAID model (95% CI 0.763 to 0.916). Comparing the AUCs, we found that FMC+PSMA SUVmax and the multivariable model were significantly more accurate for the prediction of csPC compared to PI-RADS scoring (<i>p</i> = 0.0123, <i>p</i> = 0.0253, respectively). Conclusions: Combined FMC+PSMA SUVmax seems to be a reliable parameter for the prediction of csPC and might overcome the limitations of PI-RADS scoring. Further prospective studies are necessary to confirm these promising preliminary results.https://www.mdpi.com/1718-7729/30/2/129prostate cancerPET/MRIimaging biomarkersdual tracer |
| spellingShingle | Bernhard Grubmüller Nicolai A. Huebner Sazan Rasul Paola Clauser Nina Pötsch Karl Hermann Grubmüller Marcus Hacker Sabrina Hartenbach Shahrokh F. Shariat Markus Hartenbach Pascal Baltzer Dual-Tracer PET-MRI-Derived Imaging Biomarkers for Prediction of Clinically Significant Prostate Cancer Current Oncology prostate cancer PET/MRI imaging biomarkers dual tracer |
| title | Dual-Tracer PET-MRI-Derived Imaging Biomarkers for Prediction of Clinically Significant Prostate Cancer |
| title_full | Dual-Tracer PET-MRI-Derived Imaging Biomarkers for Prediction of Clinically Significant Prostate Cancer |
| title_fullStr | Dual-Tracer PET-MRI-Derived Imaging Biomarkers for Prediction of Clinically Significant Prostate Cancer |
| title_full_unstemmed | Dual-Tracer PET-MRI-Derived Imaging Biomarkers for Prediction of Clinically Significant Prostate Cancer |
| title_short | Dual-Tracer PET-MRI-Derived Imaging Biomarkers for Prediction of Clinically Significant Prostate Cancer |
| title_sort | dual tracer pet mri derived imaging biomarkers for prediction of clinically significant prostate cancer |
| topic | prostate cancer PET/MRI imaging biomarkers dual tracer |
| url | https://www.mdpi.com/1718-7729/30/2/129 |
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