Clinical trial · Observational
Super-fast 3T Prostate MRI Using High Gradient Strength and Deep Learning
Super-fast 3T Prostate MRI Using High Gradient Strength and Deep Learning: Initial Experience
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
Recent developments in MRI techniques allow ultra-high gradient strength diffusion imaging and deep learning (DL) reconstruction in clinical routine. However, its usability in biparametric MRI (bpMRI) of the prostate has not been well studied. The aim is to establish a super-fast 3-minutes bpMRI protocol at 3 Tesla using high gradient strength and DL reconstruction and compare it against a full, multiparametric MRI (mpMRI) protocol.
Conditions
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Prostate Cancer | Malignant Prostate Neoplasm | CURATED_EXACT | 0.92 |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| MRI of the prostate | Device | — | UNRESOLVED |
Design
Arms and outcomes
Arms (0)
[]Primary outcomes (3)
- measure
- Agreement of PI-RADS scores
- timeFrame
- January - February 2024
- description
- Three radiologists with 3, 11 and 12 years of experience in prostate MRI read separately and blinded to personal and clinical parameters (name, age, patient history, value of the prostate specific antigen, clinical examination and transrectal ultrasound) the full bpMRI protocol and graded the lesions according to the PI-RADS classification. Per patient, only the highest graded lesion and its respective prostate zone was noted. If there were two distinct lesions with the highest PI-RADS score in both the peripheral and transitional zone, both were noted. After a washout period of one month all readers did the same for the mpMRI protocol. Both the agreement of biparametric and multiparametric MRI PI-RADS scores for the whole prostate, and for the specific zonal distribution (peripheral and transitional zone) were assessed by calculation of Cohens's κ, interpreted as follows: \<0.5 = poor; 0.5-0.75 = moderate; 0.75-0.9 = good; \>0.9 = excellent.
- measure
- Acquisition time
- timeFrame
- January - February 2024
- description
- Acquisition times for the whole biparametric and whole multiparametric protocol was measured.
- measure
Eligibility
Eligibility (as posted)
- Sex
- Male
- Minimum age
- 18 Years
Show eligibility criteria text
Inclusion Criteria: * Elevated PSA \>4ng/ml or suspicious digitial rectal exam or supicious transrectal ultrasound Exclusion Criteria: * General MRI contraindications (incompatible cardiac pacemaker, neurostimulators) or allergy for gadolinium-containing contrast media or severe claustrophobie
References
Publications (17)
- BACKGROUNDHugosson J, Mansson M, Wallstrom J, Axcrona U, Carlsson SV, Egevad L, Geterud K, Khatami A, Kohestani K, Pihl CG, Socratous A, Stranne J, Godtman RA, Hellstrom M; GOTEBORG-2 Trial Investigators. Prostate Cancer Screening with PSA and MRI Followed by Targeted Biopsy Only. N Engl J Med. 2022 Dec 8;387(23):2126-2137. doi: 10.1056/NEJMoa2209454. PMID 36477032
- BACKGROUNDEklund M, Jaderling F, Discacciati A, Bergman M, Annerstedt M, Aly M, Glaessgen A, Carlsson S, Gronberg H, Nordstrom T; STHLM3 consortium. MRI-Targeted or Standard Biopsy in Prostate Cancer Screening. N Engl J Med. 2021 Sep 2;385(10):908-920. doi: 10.1056/NEJMoa2100852. Epub 2021 Jul 9. PMID 34237810
- BACKGROUNDSiegel RL, Miller KD, Wagle NS, Jemal A. Cancer statistics, 2023. CA Cancer J Clin. 2023 Jan;73(1):17-48. doi: 10.3322/caac.21763. PMID 36633525
- BACKGROUNDACR, ESUR and AdMeTech Foundation. Prostate Imaging Reporting & Data System (PI-RADS). 2019. Version 2.1.
- BACKGROUNDHegde JV, Mulkern RV, Panych LP, Fennessy FM, Fedorov A, Maier SE, Tempany CM. Multiparametric MRI of prostate cancer: an update on state-of-the-art techniques and their performance in detecting and localizing prostate cancer. J Magn Reson Imaging. 2013 May;37(5):1035-54. doi: 10.1002/jmri.23860. PMID 23606141
- BACKGROUNDBischoff LM, Peeters JM, Weinhold L, Krausewitz P, Ellinger J, Katemann C, Isaak A, Weber OM, Kuetting D, Attenberger U, Pieper CC, Sprinkart AM, Luetkens JA. Deep Learning Super-Resolution Reconstruction for Fast and Motion-Robust T2-weighted Prostate MRI. Radiology. 2023 Sep;308(3):e230427. doi: 10.1148/radiol.230427. PMID 37750774
- BACKGROUNDBischoff LM, Katemann C, Isaak A, Mesropyan N, Wichtmann B, Kravchenko D, Endler C, Kuetting D, Pieper CC, Ellinger J, Weber O, Attenberger U, Luetkens JA. T2 Turbo Spin Echo With Compressed Sensing and Propeller Acquisition (Sampling k-Space by Utilizing Rotating Blades) for Fast and Motion Robust Prostate MRI: Comparison With Conventional Acquisition. Invest Radiol. 2023 Mar 1;58(3):209-215. doi: 10.1097/RLI.0000000000000923. Epub 2022 Sep 2.