Clinical trial NCT06244680: Super-fast 3T Prostate MRI Using High Gradient Strength and Deep Learning
Official title: Super-fast 3T Prostate MRI Using High Gradient Strength and Deep Learning: Initial Experience
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Prostate Cancer
Lead sponsor: University Hospital, Bonn
Sponsor class: OTHER
First posted: 2024-02-06
Enrollment: 77
Sex: MALE
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: The study population consists of male patients with clinical suspicion for prostate cancer, as described by the inclusion criteria.

Brief summary: 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.

Detailed description: Multiparametric MRI (mpMRI) of the prostate has become the most important non-invasive diagnostic tool for assessment of prostate cancer and is the baseline for MRI targeted biopsy (1,2). As the incidence of prostate cancer is high with an estimated 290,000 new cases for 2023 in the United States alone (3), the need for widespread provision of prostate mpMRI is immense. However, current clinical MRI-protocols are long with acquisition times of \>30 minutes, potentially limiting the number of examined patients. According to the guidelines of the Prostate Imaging Reporting and Data System (PI-RADS) a sufficient mpMRI protocol must include diffusion weighted imaging (DWI), T2-weighted (T2w) imaging, dynamic contrast enhanced imaging and T1-weighted imaging pre and post administration of contrast (4,5). Different approaches have been developed to shorten the protocol itself or to accelerate acquisition times. For instance, a significant reduction of T2w-sequence acquisition times was achieved by employing deep learning methods (6) or advancements of compressed sensing (7), while at the same time images had improved quality. Different studies showed equal performance of biparametric MRI (bpMRI) protocols compared to the standard multiparametric protocol, effectively reducing the acquisition time down to 5 minutes (8,9,10). This was done by focusing only on DWI and T2w imaging while omitting the dynamic contrast enhanced sequence and T1-weighted sequences, as the additional diagnostic value of these is supposed to be limited (11).

Recent developments in MRI techniques allow for ultra-high diffusion gradient strengths of up to 500 mT/m and slew rates of up to 600 T/m/s, thus reducing echo times and acquisition times by faster establishment of the diffusion gradient (12,13). Furthermore, these gradients are able to image at small scales with a high signal-to-noise ratio, consecutively enhancing sensitivity for detection of tissue microstructures (14,15). Due to the experimental nature of these gradients, this technique has only been investigated in a research setting in healthy volunteers (16), but not in a real world clinical setting, let alone in prostate imaging.

Therefore, the aim of the study was to establish a super-fast abbreviated bpMRI protocol for patients with suspicion for prostate cancer using both ultra-high gradients and deep learning reconstruction for DWI- and T2w-sequences. Besides the assessment of acquisition times, the main objective of this study was to assess the overall image quality of bpMRI and mpMRI and the influence on PI-RADS scores.

Eligibility criteria: 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

Primary outcomes:
measure: Agreement of PI-RADS scores
timeFrame: January - February 2024
measure: Acquisition time
timeFrame: January - February 2024
measure: Image quality
timeFrame: January - February 2024
Secondary outcomes:
Other outcomes:
Locations:
city: Bonn
country: Germany
facility: University Hospital Bonn, Clinic for Diagnostic and Interventional Radiology
state: NRW
Study officials:
affiliation: University of Bonn
name: Julian A Luetkens, PD Dr. med
role: PRINCIPAL_INVESTIGATOR
References:
citation: Hugosson 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.
citation: Eklund 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.
citation: Siegel 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.
citation: ACR, ESUR and AdMeTech Foundation. Prostate Imaging Reporting & Data System (PI-RADS). 2019. Version 2.1.
citation: Hegde 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.
citation: Bischoff 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.
citation: Bischoff 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.
citation: Weiss J, Martirosian P, Notohamiprodjo M, Kaufmann S, Othman AE, Grosse U, Nikolaou K, Gatidis S. Implementation of a 5-Minute Magnetic Resonance Imaging Screening Protocol for Prostate Cancer in Men With Elevated Prostate-Specific Antigen Before Biopsy. Invest Radiol. 2018 Mar;53(3):186-190. doi: 10.1097/RLI.0000000000000427.
citation: Scialpi M, Prosperi E, D'Andrea A, Martorana E, Malaspina C, Palumbo B, Orlandi A, Falcone G, Milizia M, Mearini L, Aisa MC, Scialpi P, DE Dominicis C, Bianchi G, Sidoni A. Biparametric versus Multiparametric MRI with Non-endorectal Coil at 3T in the Detection and Localization of Prostate Cancer. Anticancer Res. 2017 Mar;37(3):1263-1271. doi: 10.21873/anticanres.11443.
citation: Rais-Bahrami S, Siddiqui MM, Vourganti S, Turkbey B, Rastinehad AR, Stamatakis L, Truong H, Walton-Diaz A, Hoang AN, Nix JW, Merino MJ, Wood BJ, Simon RM, Choyke PL, Pinto PA. Diagnostic value of biparametric magnetic resonance imaging (MRI) as an adjunct to prostate-specific antigen (PSA)-based detection of prostate cancer in men without prior biopsies. BJU Int. 2015 Mar;115(3):381-8. doi: 10.1111/bju.12639. Epub 2014 Sep 15.
citation: De Visschere P, Lumen N, Ost P, Decaestecker K, Pattyn E, Villeirs G. Dynamic contrast-enhanced imaging has limited added value over T2-weighted imaging and diffusion-weighted imaging when using PI-RADSv2 for diagnosis of clinically significant prostate cancer in patients with elevated PSA. Clin Radiol. 2017 Jan;72(1):23-32. doi: 10.1016/j.crad.2016.09.011. Epub 2016 Oct 7.
citation: Huang SY, Witzel T, Keil B, Scholz A, Davids M, Dietz P, Rummert E, Ramb R, Kirsch JE, Yendiki A, Fan Q, Tian Q, Ramos-Llorden G, Lee HH, Nummenmaa A, Bilgic B, Setsompop K, Wang F, Avram AV, Komlosh M, Benjamini D, Magdoom KN, Pathak S, Schneider W, Novikov DS, Fieremans E, Tounekti S, Mekkaoui C, Augustinack J, Berger D, Shapson-Coe A, Lichtman J, Basser PJ, Wald LL, Rosen BR. Connectome 2.0: Developing the next-generation ultra-high gradient strength human MRI scanner for bridging studies of the micro-, meso- and macro-connectome. Neuroimage. 2021 Nov;243:118530. doi: 10.1016/j.neuroimage.2021.118530. Epub 2021 Aug 28.
citation: Fan Q, Eichner C, Afzali M, Mueller L, Tax CMW, Davids M, Mahmutovic M, Keil B, Bilgic B, Setsompop K, Lee HH, Tian Q, Maffei C, Ramos-Llorden G, Nummenmaa A, Witzel T, Yendiki A, Song YQ, Huang CC, Lin CP, Weiskopf N, Anwander A, Jones DK, Rosen BR, Wald LL, Huang SY. Mapping the human connectome using diffusion MRI at 300 mT/m gradient strength: Methodological advances and scientific impact. Neuroimage. 2022 Jul 1;254:118958. doi: 10.1016/j.neuroimage.2022.118958. Epub 2022 Feb 23.
citation: Setsompop K, Kimmlingen R, Eberlein E, Witzel T, Cohen-Adad J, McNab JA, Keil B, Tisdall MD, Hoecht P, Dietz P, Cauley SF, Tountcheva V, Matschl V, Lenz VH, Heberlein K, Potthast A, Thein H, Van Horn J, Toga A, Schmitt F, Lehne D, Rosen BR, Wedeen V, Wald LL. Pushing the limits of in vivo diffusion MRI for the Human Connectome Project. Neuroimage. 2013 Oct 15;80:220-33. doi: 10.1016/j.neuroimage.2013.05.078. Epub 2013 May 24.
citation: McNab JA, Edlow BL, Witzel T, Huang SY, Bhat H, Heberlein K, Feiweier T, Liu K, Keil B, Cohen-Adad J, Tisdall MD, Folkerth RD, Kinney HC, Wald LL. The Human Connectome Project and beyond: initial applications of 300 mT/m gradients. Neuroimage. 2013 Oct 15;80:234-45. doi: 10.1016/j.neuroimage.2013.05.074. Epub 2013 May 24.
citation: Huang SY, Tian Q, Fan Q, Witzel T, Wichtmann B, McNab JA, Daniel Bireley J, Machado N, Klawiter EC, Mekkaoui C, Wald LL, Nummenmaa A. High-gradient diffusion MRI reveals distinct estimates of axon diameter index within different white matter tracts in the in vivo human brain. Brain Struct Funct. 2020 May;225(4):1277-1291. doi: 10.1007/s00429-019-01961-2. Epub 2019 Sep 28.