Evaluation of prostate cancer detection using micro-ultrasound versus MRI through co-registration to whole-mount pathology.
Co-registration
Image reconstruction
MRI
Micro-ultrasound
Prostate cancer
Whole-mount pathology
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
14 08 2024
14 08 2024
Historique:
received:
29
02
2024
accepted:
08
08
2024
medline:
15
8
2024
pubmed:
15
8
2024
entrez:
14
8
2024
Statut:
epublish
Résumé
Micro-ultrasound has recently been introduced as a low-cost alternative to multi-parametric MRI for imaging prostate cancer. Early clinical studies have demonstrated promising results; however, robust validation via comparison with whole-mount pathology has yet to be achieved. Due to micro-ultrasound probe design and tissue deformation during scanning, it is difficult to accurately correlate micro-ultrasound imaging planes with ground truth whole-mount pathology slides. In this study, we developed a multi-step methodology to co-register micro-ultrasound and MRI to whole-mount pathology. The three-step process had a registration error of 3.90 ± 0.11 mm and consists of: (1) micro-ultrasound image reconstruction, (2) 3D landmark registration of micro-ultrasound to MRI, and (3) 2D capsule registration of MRI to whole-mount pathology. This process was then used in a preliminary reader study to compare the diagnostic accuracy of micro-ultrasound and MRI in 15 patients who underwent radical prostatectomy for prostate cancer. Micro-ultrasound was found to have equivalent performance to retrospective MRI review for index lesion detection (91.7% vs. 80%), while demonstrating an increased detection of tumor extent (52.5% vs. 36.7%) with similar false positive regions-of-interest (38.3% vs. 40.8%). Prospective MRI review had reduced detection of index lesions (73.3%) and tumor extent (18.9%) but improved false positive regions-of-interest (22.7%) relative to micro-ultrasound and retrospective MRI. Further evaluation is needed with a larger sample size.
Identifiants
pubmed: 39143293
doi: 10.1038/s41598-024-69804-7
pii: 10.1038/s41598-024-69804-7
doi:
Types de publication
Journal Article
Comparative Study
Langues
eng
Sous-ensembles de citation
IM
Pagination
18910Subventions
Organisme : NCI NIH HHS
ID : R01CA195505
Pays : United States
Organisme : Clinical and Translational Science Institute, University of California, Los Angeles
ID : UL1TR000124
Informations de copyright
© 2024. The Author(s).
Références
Siegel, R. L., Giaquinto, A. N. & Ahmedin, J. D. Cancer statistics, 2024. CA. Cancer J. Clin. 74, 12–49 (2024).
pubmed: 38230766
doi: 10.3322/caac.21820
Mohler, J. L. et al. Prostate cancer, version 2.2019. JNCCN J. Natl. Compr. Cancer Netw. 17, 479–505 (2019).
doi: 10.6004/jnccn.2019.0023
Klotz, L. et al. Long-term follow-up of a large active surveillance cohort of patients with prostate cancer. J. Clin. Oncol. 33, 272–277 (2015).
pubmed: 25512465
doi: 10.1200/JCO.2014.55.1192
Gleason, D. F. & Mellinger, G. T. The Veterans administration cooperative urological research group. prediction of prognosis for prostatic adenocarcinoma by combined histological grading and clinical staging. J. Urol. 111, 58–64 (1974).
pubmed: 4813554
doi: 10.1016/S0022-5347(17)59889-4
Noureldin, M. E. et al. Current techniques of prostate biopsy: An update from past to present. Trans. Androl. Urol. 9, 1510–1517 (2020).
doi: 10.21037/tau.2019.09.20
Hricak, H., Choyke, P. L., Eberhardt, S. C., Leibel, S. A. & Scardino, P. T. Imaging prostate cancer: A multidisciplinary perspective. Radiology 243, 28–53 (2007).
pubmed: 17392247
doi: 10.1148/radiol.2431030580
Stabile, A. et al. Multiparametric MRI for prostate cancer diagnosis: Current status and future directions. Nat. Rev. Urol. 17, 41–61 (2019).
pubmed: 31316185
doi: 10.1038/s41585-019-0212-4
Ahmed, H. U. et al. Diagnostic accuracy of multi-parametric MRI and TRUS biopsy in prostate cancer (PROMIS): A paired validating confirmatory study. Lancet 389, 815–822 (2017).
pubmed: 28110982
doi: 10.1016/S0140-6736(16)32401-1
Woo, S., Suh, C. H., Kim, S. Y., Cho, J. Y. & Kim, S. H. Diagnostic performance of prostate imaging reporting and data system version 2 for detection of prostate cancer: A systematic review and diagnostic meta-analysis. Eur. Urol. 72, 177–188 (2017).
pubmed: 28196723
doi: 10.1016/j.eururo.2017.01.042
Ahmed, H. U. The index lesion and the origin of prostate cancer. N. Engl. J. Med. 361, 1704–1706 (2009).
pubmed: 19846858
doi: 10.1056/NEJMcibr0905562
Bjurlin, M. A. et al. Update of the standard operating procedure on the use of multiparametric magnetic resonance imaging for the diagnosis, staging and management of prostate cancer. J. Urol. 203, 706–712 (2020).
pubmed: 31642740
doi: 10.1097/JU.0000000000000617
Arsov, C. et al. Prospective randomized trial comparing magnetic resonance imaging (MRI)-guided in-bore biopsy to MRI-ultrasound fusion and transrectal ultrasound-guided prostate biopsy in patients with prior negative biopsies. Eur. Urol. 68, 713–720 (2015).
pubmed: 26116294
doi: 10.1016/j.eururo.2015.06.008
Marks, L., Young, S. & Natarajan, S. MRI-ultrasound fusion for guidance of targeted prostate biopsy. Curr. Opin. Urol. 23, 43–50 (2013).
pubmed: 23138468
pmcid: 3581822
doi: 10.1097/MOU.0b013e32835ad3ee
Priester, A. et al. Magnetic resonance imaging underestimation of prostate cancer geometry: Use of patient specific molds to correlate images with whole mount pathology. J. Urol. 197, 320–326 (2017).
pubmed: 27484386
doi: 10.1016/j.juro.2016.07.084
Johnson, D. C. et al. Detection of individual prostate cancer foci via multiparametric magnetic resonance imaging. Eur. Urol. 75, 712–720 (2019).
pubmed: 30509763
doi: 10.1016/j.eururo.2018.11.031
Rosenkrantz, A. B. et al. Interobserver reproducibility of the PI-RADS version 2 lexicon: A multicenter study of six experienced prostate radiologists. Radiology 280, 793–804 (2016).
pubmed: 27035179
doi: 10.1148/radiol.2016152542
Foster, F. S. et al. A New 15–50 MHz array-based micro-ultrasound scanner for preclinical imaging. Ultrasound Med. Biol. 35, 1700–1708 (2009).
pubmed: 19647922
doi: 10.1016/j.ultrasmedbio.2009.04.012
McNeal, J. E., Redwine, E. A., Freiha, F. S. & Stamey, T. A. Zonal Distribution of Prostatic Adenocarcinoma: Correlation with Histologic Pattern and Direction of Spread. Am. J. Surg. Pathol. 12, 897–906 (1988).
pubmed: 3202246
doi: 10.1097/00000478-198812000-00001
Klotz, L. et al. Comparison of micro-ultrasound and multiparametric magnetic resonance imaging for prostate cancer: A multicenter, prospective analysis. Can. Urol. Assoc. J. 15, E11 (2020).
pmcid: 7769516
doi: 10.5489/cuaj.6712
Pensa, J. et al. A system for co-registration of high-resolution ultrasound, magnetic resonance imaging, and whole-mount pathology for prostate cancer. In 2021 43rd Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. 3890–3893 (2021). https://doi.org/10.1109/EMBC46164.2021.9630404
van Hove, A. et al. Comparison of image-guided targeted biopsies versus systematic randomized biopsies in the detection of prostate cancer: A systematic literature review of well-designed studies. World J. Urol. 32, 847–858 (2014).
pubmed: 24919965
doi: 10.1007/s00345-014-1332-3
Dias, A. B., O’Brien, C., Correas, J. M. & Ghai, S. Multiparametric ultrasound and micro-ultrasound in prostate cancer: A comprehensive review. Br. J. Radiol. 95, 20210633 (2022).
pubmed: 34752132
doi: 10.1259/bjr.20210633
Pallwein, L. et al. Prostate cancer diagnosis: Value of real-time elastography. Abdom. Imaging 33, 729–735 (2008).
pubmed: 18196315
doi: 10.1007/s00261-007-9345-7
Sadeghi-Naini, A. et al. Quantitative ultrasound spectroscopic imaging for characterization of disease extent in prostate cancer patients. Transl. Oncol. 8, 25–34 (2015).
pubmed: 25749174
pmcid: 4350638
doi: 10.1016/j.tranon.2014.11.005
Sano, F. & Uemura, H. The utility and limitations of contrast-enhanced ultrasound for the diagnosis and treatment of prostate cancer. Sensors 15, 4947–4957 (2015).
pubmed: 25734645
pmcid: 4435116
doi: 10.3390/s150304947
Rohrbach, D., Wodlinger, B., Wen, J., Mamou, J. & Feleppa, E. High-frequency quantitative ultrasound for imaging prostate cancer using a novel micro-ultrasound scanner. Ultrasound Med. Biol. 44, 1341–1354 (2018).
pubmed: 29627083
doi: 10.1016/j.ultrasmedbio.2018.02.014
Ghai, S. et al. Comparison of micro-US and multiparametric MRI for prostate cancer detection in biopsy-naive men. Radiology https://doi.org/10.1148/RADIOL.212163 (2022).
doi: 10.1148/RADIOL.212163
pubmed: 35852425
Ghai, S. et al. Assessing cancer risk on novel 29 MHz micro-ultrasound images of the prostate: Creation of the micro-ultrasound protocol for prostate risk identification. J. Urol. 196, 562–569 (2016).
pubmed: 26791931
doi: 10.1016/j.juro.2015.12.093
Pedraza, A. M. et al. Microultrasound in the detection of the index lesion in prostate cancer. Prostate https://doi.org/10.1002/PROS.24628 (2023).
doi: 10.1002/PROS.24628
pubmed: 37828815
Lorusso, V. et al. comparison between micro-ultrasound and multiparametric MRI regarding the correct identification of prostate cancer lesions. Clin. Genitourin. Cancer 20, e339–e345 (2022).
pubmed: 35197217
doi: 10.1016/j.clgc.2022.01.013
Priester, A. et al. Registration accuracy of patient-specific, three-dimensional-printed prostate molds for correlating pathology with magnetic resonance imaging. IEEE Trans. Biomed. Eng. 66, 14–22 (2019).
pubmed: 29993431
doi: 10.1109/TBME.2018.2828304
Fedorov, A. et al. 3D Slicer as an image computing platform for the quantitative imaging network. Magn Reson Imaging 30, 1323–1341 (2012).
pubmed: 22770690
pmcid: 3466397
doi: 10.1016/j.mri.2012.05.001
Wu, H. H. et al. A system using patient-specific 3D-printed molds to spatially align in vivo MRI with ex vivo MRI and whole-mount histopathology for prostate cancer research. J. Magn. Reson. Imaging 49, 270–279 (2019).
pubmed: 30069968
doi: 10.1002/jmri.26189
Fei, B., Kemper, C. & Wilson, D. L. A comparative study of warping and rigid body registration for the prostate and pelvic MR volumes. Comput. Med. Imaging Graph. 27, 267–281 (2003).
pubmed: 12631511
doi: 10.1016/S0895-6111(02)00093-9
Priester, A. et al. A system for evaluating magnetic resonance imaging of prostate cancer using patient-specific 3D printed molds. Am. J. Clin. Exp. Urol. 2, 127 (2014).
pubmed: 25374914
pmcid: 4219304
Schned, A. R. et al. Tissue-shrinkage correction factor in the calculation of prostate cancer volume. Am. J. Surg. Pathol. 20, 1501–1506 (1996).
pubmed: 8944043
doi: 10.1097/00000478-199612000-00009
Xu, S. et al. Real-time MRI-TRUS fusion for guidance of targeted prostate biopsies. Comput. Aided Surg. 13, 255–264 (2010).
doi: 10.3109/10929080802364645
Pensa, J., Geoghegan, R. & Natarajan, S. 3D ultrasound for biopsy of the prostate. In 3D Ultrasound (eds Pensa, J. et al.) 154–175 (CRC Press, 2023). https://doi.org/10.1201/9781003299462-11 .
doi: 10.1201/9781003299462-11
Alyami, W., Kyme, A. & Bourne, R. Histological validation of MRI: A review of challenges in registration of imaging and whole-mount histopathology. J. Magn. Reson. Imaging 55, 11–22 (2022).
pubmed: 33128424
doi: 10.1002/jmri.27409
Callejas, M. F. et al. Detection of clinically significant index prostate cancer using micro-ultrasound: Correlation with radical prostatectomy. Urology 169, 150–155 (2022).
pubmed: 35843353
doi: 10.1016/j.urology.2022.07.002
Wiemer, L. et al. Evolution of targeted prostate biopsy by adding micro-ultrasound to the magnetic resonance imaging pathway. Eur. Urol. Focus 7, 1292–1299 (2021).
pubmed: 32654967
doi: 10.1016/j.euf.2020.06.022
Lughezzani, G. et al. Comparison of the diagnostic accuracy of micro-ultrasound and magnetic resonance imaging/ultrasound fusion targeted biopsies for the diagnosis of clinically significant prostate cancer. Eur. Urol. Oncol. 2, 329–332 (2019).
pubmed: 31200848
doi: 10.1016/j.euo.2018.10.001
Turkbey, B. et al. Prostate cancer: Value of multiparametric mr imaging at 3 T for detection—histopathologic correlation. Radiology 255, 89 (2010).
pubmed: 20308447
pmcid: 2843833
doi: 10.1148/radiol.09090475
Priester, A. et al. Prediction and mapping of intraprostatic tumor extent with artificial intelligence. Eur. Urol. Open Sci. 54, 20–27 (2023).
pubmed: 37545845
pmcid: 10403686
doi: 10.1016/j.euros.2023.05.018
Pavlovich, C. P. et al. A multi-institutional randomized controlled trial comparing first-generation transrectal high-resolution micro-ultrasound with conventional frequency transrectal ultrasound for prostate biopsy. BJUI Compass 2, 126 (2021).
pubmed: 35474889
doi: 10.1002/bco2.59
Nahar, B. et al. Prospective evaluation of focal high intensity focused ultrasound for localized prostate cancer. J. Urol. 204, 483–489 (2020).
pubmed: 32167866
doi: 10.1097/JU.0000000000001015
Geoghegan, R. et al. Interstitial optical monitoring of focal laser ablation. IEEE Trans. Biomed. Eng. https://doi.org/10.1109/TBME.2022.3150279 (2022).
doi: 10.1109/TBME.2022.3150279
pubmed: 35148260
pmcid: 9371599
Natarajan, S. et al. Focal laser ablation of prostate cancer: Feasibility of magnetic resonance imaging-ultrasound fusion for guidance. J. Urol. 198, 839–847 (2017).
pubmed: 28396184
doi: 10.1016/j.juro.2017.04.017
Ittmann, M. Anatomy and histology of the human and murine prostate. Cold Spring Harb. Perspect. Med. 8, a030346 (2018).
pubmed: 29038334
pmcid: 5932577
doi: 10.1101/cshperspect.a030346
Li, H. et al. Machine learning in prostate MRI for prostate cancer: Current status and future opportunities. Diagnostics 12, 289 (2022).
pubmed: 35204380
pmcid: 8870978
doi: 10.3390/diagnostics12020289
Gilany, M. et al. Towards Confident Detection of Prostate Cancer using High Resolution Micro-ultrasound (Springer, 2022).
doi: 10.1007/978-3-031-16440-8_40
Gilany, M. et al. TRUSformer: improving prostate cancer detection from micro-ultrasound using attention and self-supervision. Int. J. Comput. Assist. Radiol. Surg. 18, 1193–1200 (2023).
pubmed: 37217768
doi: 10.1007/s11548-023-02949-4
Wilson, P. F. R. et al. Self-supervised learning with limited labeled data for prostate cancer detection in high-frequency ultrasound. IEEE Trans. Ultrason. Ferroelectr. Freq. Control 70, 1073–1083 (2023).
pubmed: 37478033
doi: 10.1109/TUFFC.2023.3297840