Prostate Cancer3DmpUS for PCaNCT04605276
Threedimensional Multiparametric Ultrasound for Prostate Cancer Detection
An observational study of Prostate Cancer, run by Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA) at 3 sites in Netherlands.
Trial summary
Rationale: Current imaging techniques for the detection and grading of prostate cancer are imperfect, leading to unnecessary biopsies, suboptimal treatment decisions and missed clinically significant cancers. Read more about this study
- Who is it for?
- Ages 18 years and older, men only
- Conditions the study is for
- Prostate Cancer
- How many people
- 608 participants
- Where
- 3 sitesNetherlands
- Study dates
- 28 Jun 2021to 7 Mar 2024
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- Men only
- No healthy volunteers
- Adult, Older adult
Study population: 1. Male patients of age ≥18 suspected for prostate cancer who are scheduled for systematic and/or targeted biopsy after mpMRI examination. 2. patients of age ≥18 with confirmed prostate cancer who are scheduled for radical prostatectomy.
Who may be able to join
- In order to be eligible to participate in this study, a subject must meet all of the following criteria:
- Men ≥18 years with a clinical suspicion of prostate cancer or confirmed prostate cancer.
- Scheduled for either systematic and/or targeted biopsy after mpMRI examination or radical prostatectomy
- Signed informed consent
Who cannot join
- A potential subject who meets any of the following criteria will be excluded from participation in this study:
- No mpMRI performed prior to prostate biopsy or radical prostatectomy
- A history of chemotherapy for PCa or currently being treated with chemotherapy for PCa.
- A patient history that includes any of the following prostate related interventions:
- Brachytherapy or external radiotherapy for PCa;
- Focal therapy for prostate cancer;
Show all 12Show fewer
- Prostate biopsy within the last 30 days.
- Hormonal therapy for prostate cancer within the last six months
- A patient history with a cardiac right to left shunt.
- Current treatment with dobutamine
- Known severe pulmonary hypertension (pulmonary artery pressure >90 mmHg), uncontrolled systemic hypertension or respiratory distress syndrome
- Incapable of understanding the language in which the patient information is given.
Trial locations and contacts
3 sites in 1 country.
Netherlands3 sites
Netherlands Cancer Institute
Amsterdam, North Holland, 1066 CX
Amsterdam Univesity Medical Centers location VUmc
Amsterdam, North Holland, 1081HV
Academic Medical Center
Amsterdam, North Holland, 1105AZ
About this study
Official title: Improving the AI-based Image Analysis Algorithm for 3D Multiparametric Ultrasound for the Detection, Grading and Localization of Prostate Cancer
Rationale: Current imaging techniques for the detection and grading of prostate cancer are imperfect, leading to unnecessary biopsies, suboptimal treatment decisions and missed clinically significant cancers. The hypothesis of this study is that computer assisted analysis of 3D multiparametric ultrasound (mpUS) images can accurately detect, grade and localize prostate cancer. 3D mpUS may then become a more cost-effective and more streamlined imaging strategy than the current standard: mpMRI.
Objective: The primary objective is to collect high-quality 3D mpUS and histology data, to train and improve the classifier algorithm with the goal of achieving an accurate ultrasound imaging tool for the detection of clinically significant prostate cancer.
Read more
Secondary objectives are related to the preliminary assessment of the performance of 3D mpUS with computer assisted analysis.
Study design: This is a prospective, multi-center study in men with a suspicion of prostate cancer who are scheduled for prostate biopsies, and men with confirmed prostate cancer who are scheduled to undergo a radical prostatectomy. Prior to prostate biopsies or the radical prostatectomy, 3D mpUS imaging will be performed. The ultrasound images will be analyzed and used for algorithm training using the biopsies and/or prostatecomy specimens as gold standard. Additional research coupes of pathology material (both biopsies and radical prostatectomy specimens) from study subjects will be anonymized and separately analyzed and stored in a central, independent institution. The outcome of the 3D mpUS analysis and the additional pathology evaluation are for research purposes only and will not interfere with standard patient care.
Study population: 1) Male patients of age ≥18 suspected for prostate cancer who are scheduled for systematic and/or targeted biopsy after mpMRI examination.
- patients of age ≥18 with confirmed prostate cancer who are scheduled for radical prostatectomy.
Main study parameters/endpoints:
- Gleason/Grade group scoring based on histology. Using histology as the reference standard the accuracy of the algorithm will be optimized to be differentiating between benign tissue and various grades of malignancy.
- Localization and size of lesions at full-gland histology in the subset of patients undergoing radical prostatectomy. Correlation in tumour size and location will be optimized between 3D mpUS findings and histology of the full gland.
For the secondary objective, preliminary assessment of the performance of 3D mpUS, the following endpoints are evaluated
- Among all clinically significant detected cancers confirmed by histology, the proportion of these cancers that would have been detected by 3D mpUS will be calculated. The number of false positive findings by 3D mpUS both as an absolute count and expressed as a mean rate per patient.
- The concordance in the detection and grading of abnormalities between mpMRI and 3D mpUS by examining the frequency and type of disagreements and calculating the kappa statistic.
- Conditions
- Prostate Cancer
- Being tested
- No intervention
- Keywords
- Contrast Enhanced Ultrasound, CEUS, Machine Learning, Artificial Intelligence, Multiparametric Ultrasound
- Medical subject headings
- Prostatic Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
No interventionOther
No intervention
| Study group | Role | What they receive |
|---|---|---|
| Pre-biopsy cohort | Male patients of age ≥18 suspected for prostate cancer who are scheduled for systematic and/or targeted biopsy after mpMRI examination.
No intervention study Receives: Other: No intervention | |
| Pre-radical prostatectomy cohort | Male patients of age ≥18 diagnosed with prostate cancer who are scheduled for radical prostatectomy Receives: Other: No intervention |
What is being measured
The primary outcome is the main question the study is designed to answer.
To collect high quality 3D multiparametric ultrasound and histology data to train and improve the classifier algorithm with the goal of achieving an accurate ultrasound imaging tool for detection, grading and localization of prostate cancer.
This is a diagnostic accuracy study with cross-sectional interest between 3D multiparametric ultrasound results and histological findings at biopsy or histological examination of the full grand as the reference standards.
Measured: The 3D multiparametric ultrasound images collected te moment the ultrasound is done. Histology findings will be collected 2 week after prostatebiopsies or radical prostatectomy. No patient follow-up is needed.
Secondary outcomes (3)
The number of histologically proven clinically relevant cancer that can be detected by 3D multiparametric ultrasound using full mount prostate histopathology as the reference standard.
Sensitivity / Negative predictive value
Measured: The 3D multiparametric ultrasound images collected the moment the ultrasound is done. Histology findings will be collected 2 week after prostatebiopsies or radical prostatectomy. No patient follow-up is needed.
The frequency of false-positive result by 3D multiparametric ultrasound using full mount prostate histopathology as the reference standard.
Specificity / Positive Predictive Value
Measured: The 3D multiparametric ultrasound images collected the moment the ultrasound is done. Histology findings will be collected 2 week after prostatebiopsies or radical prostatectomy. No patient follow-up is needed.
The concordance between findings from mpMRI and 3D multiparametric ultrasound.
Cancer detection rates, relative sensitivity / specificity
Measured: mpMRI is present at time of inclusion, 3D mpUS images will be collected 1-3 weeks after inclusion. The concordance between mpMRI and 3DmpUS can be evaluated after imaging and histpathology data is in.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted28 Oct 2020
- Study start28 Jun 2021
- Primary completion4 Mar 2024
- Study completion7 Mar 2024
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (11)Papers the sponsor has linked to this study.
- Other trials for Prostate CancerStudies of the same condition, open and under way.
- More trials run by Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA)The sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 608 participants (actual)
Sponsor and investigators
- Sponsor type
- University, hospital or other
- Collaborators
- Angiogenesis Analytics
- Responsible party
- Principal investigator, Harrie P. Beerlage, Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA)
- Investigators
- Harrie Beerlage, Professor, Principal investigator, Amsterdam UMC, location VUmc
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04605276
- Sponsor's protocol ID
- CUDI - PCa
- Acronym
- 3DmpUS for PCa
- Status last verified
- Mar 2024
- First submitted
- 15 Oct 2020
- Last updated
- 15 Oct 2024
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Publications
van Moorselaar RJ, Voest EE. Angiogenesis in prostate cancer: its role in disease progression and possible therapeutic approaches. Mol Cell Endocrinol. 2002 Nov 29;197(1-2):239-50. doi: 10.1016/s0303-7207(02)00262-9.
PubMed 12431818Russo G, Mischi M, Scheepens W, De la Rosette JJ, Wijkstra H. Angiogenesis in prostate cancer: onset, progression and imaging. BJU Int. 2012 Dec;110(11 Pt C):E794-808. doi: 10.1111/j.1464-410X.2012.11444.x. Epub 2012 Sep 7.
PubMed 22958524Mischi M, Kuenen MP, Wijkstra H. Angiogenesis imaging by spatiotemporal analysis of ultrasound contrast agent dispersion kinetics. IEEE Trans Ultrason Ferroelectr Freq Control. 2012 Apr;59(4):621-9. doi: 10.1109/TUFFC.2012.2241.
PubMed 22547274Kuenen MP, Saidov TA, Wijkstra H, de la Rosette JJ, Mischi M. Spatiotemporal correlation of ultrasound contrast agent dilution curves for angiogenesis localization by dispersion imaging. IEEE Trans Ultrason Ferroelectr Freq Control. 2013 Dec;60(12):2665-9. doi: 10.1109/TUFFC.2013.2865.
PubMed 24297031Postema AW, Frinking PJ, Smeenge M, De Reijke TM, De la Rosette JJ, Tranquart F, Wijkstra H. Dynamic contrast-enhanced ultrasound parametric imaging for the detection of prostate cancer. BJU Int. 2016 Apr;117(4):598-603. doi: 10.1111/bju.13116. Epub 2015 Jun 29.
PubMed 25754526Postema AW, Gayet MCW, van Sloun RJG, Wildeboer RR, Mannaerts CK, Savci-Heijink CD, Schalk SG, Kajtazovic A, van der Poel H, Mulders PFA, Beerlage HP, Mischi M, Wijkstra H. Contrast-enhanced ultrasound with dispersion analysis for the localization of prostate cancer: correlation with radical prostatectomy specimens. World J Urol. 2020 Nov;38(11):2811-2818. doi: 10.1007/s00345-020-03103-4. Epub 2020 Feb 20.
PubMed 32078707Mannaerts CK, Engelbrecht MRW, Postema AW, van Kollenburg RAA, Hoeks CMA, Savci-Heijink CD, Van Sloun RJG, Wildeboer RR, De Reijke TM, Mischi M, Wijkstra H. Detection of clinically significant prostate cancer in biopsy-naive men: direct comparison of systematic biopsy, multiparametric MRI- and contrast-ultrasound-dispersion imaging-targeted biopsy. BJU Int. 2020 Oct;126(4):481-493. doi: 10.1111/bju.15093. Epub 2020 May 13.
PubMed 32315112Mannaerts CK, Wildeboer RR, Remmers S, van Kollenburg RAA, Kajtazovic A, Hagemann J, Postema AW, van Sloun RJG, J Roobol M, Tilki D, Mischi M, Wijkstra H, Salomon G. Multiparametric Ultrasound for Prostate Cancer Detection and Localization: Correlation of B-mode, Shear Wave Elastography and Contrast Enhanced Ultrasound with Radical Prostatectomy Specimens. J Urol. 2019 Dec;202(6):1166-1173. doi: 10.1097/JU.0000000000000415. Epub 2019 Jun 27.
PubMed 31246546van den Kroonenberg DL, Delberghe F, Jager A, Postema AW, de Bie KCC, Reitsma JB, Zwart M, Wijkstra H, Garrido-Utrilla A, de Baaij J, van Basten JA, van der Poel HG, Beerlage HP, Mischi M, Oddens JR. Evaluation of an artificial intelligence model based on multiparametric transrectal ultrasound for localizing clinically significant prostate cancer by simulation of targeted biopsies. Eur Radiol. 2026 Apr;36(4):3043-3049. doi: 10.1007/s00330-025-12114-x. Epub 2025 Nov 6.
PubMed 41196365van den Kroonenberg DL, Delberghe FT, Jager A, Postema AW, Beerlage HP, Zwart W, Mischi M, Oddens JR. Development and Validation of an Algorithm for Segmentation of the Prostate and its Zones from Three-dimensional Transrectal Multiparametric Ultrasound Images. Eur Urol Open Sci. 2025 Apr 6;75:48-54. doi: 10.1016/j.euros.2025.03.005. eCollection 2025 May.
PubMed 40241852van den Kroonenberg DL, Went J, Jager A, Garrido-Utrilla A, Trappenburg JCA, Postema AW, Beerlage HP, Oddens JR. Developing a training for 3D transrectal multiparametric ultrasound of the prostate: a human factors engineering approach. Expert Rev Med Devices. 2025 Apr;22(4):361-367. doi: 10.1080/17434440.2025.2473632. Epub 2025 Mar 6.
PubMed 40040313
Study at a glance
From the registry record, last updated by the sponsor on 15 Oct 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Improving the AI-based Image Analysis Algorithm for 3D Multiparametric Ultrasound for the Detection, Grading and Localization of Prostate Cancer
- ClinicalTrials.gov ID
- NCT04605276
- Acronym / sponsor ID
- 3DmpUS for PCa / CUDI - PCa
- Conditions
- Prostate Cancer
- Keywords
- Contrast Enhanced Ultrasound, CEUS, Machine Learning, Artificial Intelligence, Multiparametric Ultrasound
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 608 participants (actual)
- Lead sponsor
- Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA)University, hospital or other
- Collaborators
- Angiogenesis Analytics
- Study start
- 28 Jun 2021 (actual)
- Primary completion
- 4 Mar 2024 (actual)
- Study completion
- 7 Mar 2024 (actual)
- First posted
- 28 Oct 2020 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Rationale: Current imaging techniques for the detection and grading of prostate cancer are imperfect, leading to unnecessary biopsies, suboptimal treatment decisions and missed clinically significant cancers. The hypothesis of this study is that computer assisted analysis of 3D multiparametric ultrasound (mpUS) images can accurately detect, grade and localize prostate cancer. 3D mpUS may then become a more cost-effective and more streamlined imaging strategy than the current standard: mpMRI.
Objective: The primary objective is to collect high-quality 3D mpUS and histology data, to train and improve the classifier algorithm with the goal of achieving an accurate ultrasound imaging tool for the detection of clinically significant prostate cancer.
Secondary objectives are related to the preliminary assessment of the performance of 3D mpUS with computer assisted analysis.
Study design: This is a prospective, multi-center study in men with a suspicion of prostate cancer who are scheduled for prostate biopsies, and men with confirmed prostate cancer who are scheduled to undergo a radical prostatectomy. Prior to prostate biopsies or the radical prostatectomy, 3D mpUS imaging will be performed. The ultrasound images will be analyzed and used for algorithm training using the biopsies and/or prostatecomy specimens as gold standard. Additional research coupes of pathology material (both biopsies and radical prostatectomy specimens) from study subjects will be anonymized and separately analyzed and stored in a central, independent institution. The outcome of the 3D mpUS analysis and the additional pathology evaluation are for research purposes only and will not interfere with standard patient care.
Study population: 1) Male patients of age ≥18 suspected for prostate cancer who are scheduled for systematic and/or targeted biopsy after mpMRI examination.
- patients of age ≥18 with confirmed prostate cancer who are scheduled for radical prostatectomy.
Main study parameters/endpoints:
- Gleason/Grade group scoring based on histology. Using histology as the reference standard the accuracy of the algorithm will be optimized to be differentiating between benign tissue and various grades of malignancy.
- Localization and size of lesions at full-gland histology in the subset of patients undergoing radical prostatectomy. Correlation in tumour size and location will be optimized between 3D mpUS findings and histology of the full gland.
For the secondary objective, preliminary assessment of the performance of 3D mpUS, the following endpoints are evaluated
- Among all clinically significant detected cancers confirmed by histology, the proportion of these cancers that would have been detected by 3D mpUS will be calculated. The number of false positive findings by 3D mpUS both as an absolute count and expressed as a mean rate per patient.
- The concordance in the detection and grading of abnormalities between mpMRI and 3D mpUS by examining the frequency and type of disagreements and calculating the kappa statistic.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Pre-biopsy cohort | – | Other: No interventionMale patients of age ≥18 suspected for prostate cancer who are scheduled for systematic and/or targeted biopsy after mpMRI examination. No intervention study |
| Pre-radical prostatectomy cohort | – | Other: No interventionMale patients of age ≥18 diagnosed with prostate cancer who are scheduled for radical prostatectomy |
Who may qualify
- Ages
- 18 years and older
- Sex
- Male only
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- 1. Male patients of age ≥18 suspected for prostate cancer who are scheduled for systematic and/or targeted biopsy after mpMRI examination. 2. patients of age ≥18 with confirmed prostate cancer who are scheduled for radical prostatectomy.
Key inclusion criteria (4 listed)
- In order to be eligible to participate in this study, a subject must meet all of the following criteria:
- Men ≥18 years with a clinical suspicion of prostate cancer or confirmed prostate cancer.
- Scheduled for either systematic and/or targeted biopsy after mpMRI examination or radical prostatectomy
- Signed informed consent
Key exclusion criteria (12 listed)
- A potential subject who meets any of the following criteria will be excluded from participation in this study:
- No mpMRI performed prior to prostate biopsy or radical prostatectomy
- A history of chemotherapy for PCa or currently being treated with chemotherapy for PCa.
- A patient history that includes any of the following prostate related interventions:
- Hormonal therapy for prostate cancer within the last six months
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| No interventionNo intervention | Other | Pre-biopsy cohort, Pre-radical prostatectomy cohort |
Primary outcome
To collect high quality 3D multiparametric ultrasound and histology data to train and improve the classifier algorithm with the goal of achieving an accurate ultrasound imaging tool for detection, grading and localization of prostate cancer.
Time frame: The 3D multiparametric ultrasound images collected te moment the ultrasound is done. Histology findings will be collected 2 week after prostatebiopsies or radical prostatectomy. No patient follow-up is needed.
This is a diagnostic accuracy study with cross-sectional interest between 3D multiparametric ultrasound results and histological findings at biopsy or histological examination of the full grand as the reference standards.
3 secondary outcomes
The number of histologically proven clinically relevant cancer that can be detected by 3D multiparametric ultrasound using full mount prostate histopathology as the reference standard.
Time frame: The 3D multiparametric ultrasound images collected the moment the ultrasound is done. Histology findings will be collected 2 week after prostatebiopsies or radical prostatectomy. No patient follow-up is needed.
The frequency of false-positive result by 3D multiparametric ultrasound using full mount prostate histopathology as the reference standard.
Time frame: The 3D multiparametric ultrasound images collected the moment the ultrasound is done. Histology findings will be collected 2 week after prostatebiopsies or radical prostatectomy. No patient follow-up is needed.
The concordance between findings from mpMRI and 3D multiparametric ultrasound.
Time frame: mpMRI is present at time of inclusion, 3D mpUS images will be collected 1-3 weeks after inclusion. The concordance between mpMRI and 3DmpUS can be evaluated after imaging and histpathology data is in.
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 15 Oct 2024.
- Background: PubMed 12431818van Moorselaar RJ, Voest EE. Angiogenesis in prostate cancer: its role in disease progression and possible therapeutic approaches. Mol Cell Endocrinol. 2002 Nov 29;197(1-2):239-50. doi: 10.1016/s0303-7207(02)00262-9.
- Results publication: PubMed 22958524Russo G, Mischi M, Scheepens W, De la Rosette JJ, Wijkstra H. Angiogenesis in prostate cancer: onset, progression and imaging. BJU Int. 2012 Dec;110(11 Pt C):E794-808. doi: 10.1111/j.1464-410X.2012.11444.x. Epub 2012 Sep 7.
- Results publication: PubMed 22547274Mischi M, Kuenen MP, Wijkstra H. Angiogenesis imaging by spatiotemporal analysis of ultrasound contrast agent dispersion kinetics. IEEE Trans Ultrason Ferroelectr Freq Control. 2012 Apr;59(4):621-9. doi: 10.1109/TUFFC.2012.2241.
- Results publication: PubMed 24297031Kuenen MP, Saidov TA, Wijkstra H, de la Rosette JJ, Mischi M. Spatiotemporal correlation of ultrasound contrast agent dilution curves for angiogenesis localization by dispersion imaging. IEEE Trans Ultrason Ferroelectr Freq Control. 2013 Dec;60(12):2665-9. doi: 10.1109/TUFFC.2013.2865.
- Results publication: PubMed 25754526Postema AW, Frinking PJ, Smeenge M, De Reijke TM, De la Rosette JJ, Tranquart F, Wijkstra H. Dynamic contrast-enhanced ultrasound parametric imaging for the detection of prostate cancer. BJU Int. 2016 Apr;117(4):598-603. doi: 10.1111/bju.13116. Epub 2015 Jun 29.
- Results publication: PubMed 32078707Postema AW, Gayet MCW, van Sloun RJG, Wildeboer RR, Mannaerts CK, Savci-Heijink CD, Schalk SG, Kajtazovic A, van der Poel H, Mulders PFA, Beerlage HP, Mischi M, Wijkstra H. Contrast-enhanced ultrasound with dispersion analysis for the localization of prostate cancer: correlation with radical prostatectomy specimens. World J Urol. 2020 Nov;38(11):2811-2818. doi: 10.1007/s00345-020-03103-4. Epub 2020 Feb 20.
- Results publication: PubMed 32315112Mannaerts CK, Engelbrecht MRW, Postema AW, van Kollenburg RAA, Hoeks CMA, Savci-Heijink CD, Van Sloun RJG, Wildeboer RR, De Reijke TM, Mischi M, Wijkstra H. Detection of clinically significant prostate cancer in biopsy-naive men: direct comparison of systematic biopsy, multiparametric MRI- and contrast-ultrasound-dispersion imaging-targeted biopsy. BJU Int. 2020 Oct;126(4):481-493. doi: 10.1111/bju.15093. Epub 2020 May 13.
- Results publication: PubMed 31246546Mannaerts CK, Wildeboer RR, Remmers S, van Kollenburg RAA, Kajtazovic A, Hagemann J, Postema AW, van Sloun RJG, J Roobol M, Tilki D, Mischi M, Wijkstra H, Salomon G. Multiparametric Ultrasound for Prostate Cancer Detection and Localization: Correlation of B-mode, Shear Wave Elastography and Contrast Enhanced Ultrasound with Radical Prostatectomy Specimens. J Urol. 2019 Dec;202(6):1166-1173. doi: 10.1097/JU.0000000000000415. Epub 2019 Jun 27.
- Derived from this study: PubMed 41196365van den Kroonenberg DL, Delberghe F, Jager A, Postema AW, de Bie KCC, Reitsma JB, Zwart M, Wijkstra H, Garrido-Utrilla A, de Baaij J, van Basten JA, van der Poel HG, Beerlage HP, Mischi M, Oddens JR. Evaluation of an artificial intelligence model based on multiparametric transrectal ultrasound for localizing clinically significant prostate cancer by simulation of targeted biopsies. Eur Radiol. 2026 Apr;36(4):3043-3049. doi: 10.1007/s00330-025-12114-x. Epub 2025 Nov 6.
- Derived from this study: PubMed 40241852van den Kroonenberg DL, Delberghe FT, Jager A, Postema AW, Beerlage HP, Zwart W, Mischi M, Oddens JR. Development and Validation of an Algorithm for Segmentation of the Prostate and its Zones from Three-dimensional Transrectal Multiparametric Ultrasound Images. Eur Urol Open Sci. 2025 Apr 6;75:48-54. doi: 10.1016/j.euros.2025.03.005. eCollection 2025 May.
- Derived from this study: PubMed 40040313van den Kroonenberg DL, Went J, Jager A, Garrido-Utrilla A, Trappenburg JCA, Postema AW, Beerlage HP, Oddens JR. Developing a training for 3D transrectal multiparametric ultrasound of the prostate: a human factors engineering approach. Expert Rev Med Devices. 2025 Apr;22(4):361-367. doi: 10.1080/17434440.2025.2473632. Epub 2025 Mar 6.
- Individual participant dataSharing planned: Undecided
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Harrie Beerlage, Professor principal investigator
Amsterdam UMC, location VUmc
3 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Prostate Cancer, run by Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA) at 3 sites in Netherlands.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 12 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 15 Oct 2024. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 3 sites in Netherlands. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
To collect high quality 3D multiparametric ultrasound and histology data to train and improve the classifier algorithm with the goal of achieving an accurate ultrasound imaging tool for detection, grading and localization of prostate cancer. (time frame: The 3D multiparametric ultrasound images collected te moment the ultrasound is done. Histology findings will be collected 2 week after prostatebiopsies or radical prostatectomy. No patient follow-up is needed.). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT04605276, which also lists 11 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 15 Oct 2024.