Joint estimation of relaxation and diffusion tissue parameters for prostate cancer with relaxation-VERDICT MRI
Abstract This work presents a biophysical model of diffusion and relaxation MRI for prostate called relaxation vascular, extracellular and restricted diffusion for cytometry in tumours (rVERDICT). The model includes compartment-specific relaxation effects providing T1/T2 estimates and microstructura...
| Main Authors: | , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-02-01
|
| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-30182-1 |
| _version_ | 1797864718253162496 |
|---|---|
| author | Marco Palombo Vanya Valindria Saurabh Singh Eleni Chiou Francesco Giganti Hayley Pye Hayley C. Whitaker David Atkinson Shonit Punwani Daniel C. Alexander Eleftheria Panagiotaki |
| author_facet | Marco Palombo Vanya Valindria Saurabh Singh Eleni Chiou Francesco Giganti Hayley Pye Hayley C. Whitaker David Atkinson Shonit Punwani Daniel C. Alexander Eleftheria Panagiotaki |
| author_sort | Marco Palombo |
| collection | DOAJ |
| description | Abstract This work presents a biophysical model of diffusion and relaxation MRI for prostate called relaxation vascular, extracellular and restricted diffusion for cytometry in tumours (rVERDICT). The model includes compartment-specific relaxation effects providing T1/T2 estimates and microstructural parameters unbiased by relaxation properties of the tissue. 44 men with suspected prostate cancer (PCa) underwent multiparametric MRI (mp-MRI) and VERDICT-MRI followed by targeted biopsy. We estimate joint diffusion and relaxation prostate tissue parameters with rVERDICT using deep neural networks for fast fitting. We tested the feasibility of rVERDICT estimates for Gleason grade discrimination and compared with classic VERDICT and the apparent diffusion coefficient (ADC) from mp-MRI. The rVERDICT intracellular volume fraction fic discriminated between Gleason 3 + 3 and 3 + 4 (p = 0.003) and Gleason 3 + 4 and ≥ 4 + 3 (p = 0.040), outperforming classic VERDICT and the ADC from mp-MRI. To evaluate the relaxation estimates we compare against independent multi-TE acquisitions, showing that the rVERDICT T2 values are not significantly different from those estimated with the independent multi-TE acquisition (p > 0.05). Also, rVERDICT parameters exhibited high repeatability when rescanning five patients (R2 = 0.79–0.98; CV = 1–7%; ICC = 92–98%). The rVERDICT model allows for accurate, fast and repeatable estimation of diffusion and relaxation properties of PCa sensitive enough to discriminate Gleason grades 3 + 3, 3 + 4 and ≥ 4 + 3. |
| first_indexed | 2024-04-09T22:57:38Z |
| format | Article |
| id | doaj.art-be152874c18a46fdbab712a92fa8a29f |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-09T22:57:38Z |
| publishDate | 2023-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-be152874c18a46fdbab712a92fa8a29f2023-03-22T11:12:57ZengNature PortfolioScientific Reports2045-23222023-02-0113111310.1038/s41598-023-30182-1Joint estimation of relaxation and diffusion tissue parameters for prostate cancer with relaxation-VERDICT MRIMarco Palombo0Vanya Valindria1Saurabh Singh2Eleni Chiou3Francesco Giganti4Hayley Pye5Hayley C. Whitaker6David Atkinson7Shonit Punwani8Daniel C. Alexander9Eleftheria Panagiotaki10Centre for Medical Image Computing, Department of Computer Science, University College LondonCentre for Medical Image Computing, Department of Computer Science, University College LondonCentre for Medical Imaging, University College LondonCentre for Medical Image Computing, Department of Computer Science, University College LondonDivision of Surgery and Interventional Science, University College LondonMolecular Diagnostics and Therapeutics Group, Division of Surgery & Interventional Science, University College LondonMolecular Diagnostics and Therapeutics Group, Division of Surgery & Interventional Science, University College LondonCentre for Medical Imaging, University College LondonCentre for Medical Imaging, University College LondonCentre for Medical Image Computing, Department of Computer Science, University College LondonCentre for Medical Image Computing, Department of Computer Science, University College LondonAbstract This work presents a biophysical model of diffusion and relaxation MRI for prostate called relaxation vascular, extracellular and restricted diffusion for cytometry in tumours (rVERDICT). The model includes compartment-specific relaxation effects providing T1/T2 estimates and microstructural parameters unbiased by relaxation properties of the tissue. 44 men with suspected prostate cancer (PCa) underwent multiparametric MRI (mp-MRI) and VERDICT-MRI followed by targeted biopsy. We estimate joint diffusion and relaxation prostate tissue parameters with rVERDICT using deep neural networks for fast fitting. We tested the feasibility of rVERDICT estimates for Gleason grade discrimination and compared with classic VERDICT and the apparent diffusion coefficient (ADC) from mp-MRI. The rVERDICT intracellular volume fraction fic discriminated between Gleason 3 + 3 and 3 + 4 (p = 0.003) and Gleason 3 + 4 and ≥ 4 + 3 (p = 0.040), outperforming classic VERDICT and the ADC from mp-MRI. To evaluate the relaxation estimates we compare against independent multi-TE acquisitions, showing that the rVERDICT T2 values are not significantly different from those estimated with the independent multi-TE acquisition (p > 0.05). Also, rVERDICT parameters exhibited high repeatability when rescanning five patients (R2 = 0.79–0.98; CV = 1–7%; ICC = 92–98%). The rVERDICT model allows for accurate, fast and repeatable estimation of diffusion and relaxation properties of PCa sensitive enough to discriminate Gleason grades 3 + 3, 3 + 4 and ≥ 4 + 3.https://doi.org/10.1038/s41598-023-30182-1 |
| spellingShingle | Marco Palombo Vanya Valindria Saurabh Singh Eleni Chiou Francesco Giganti Hayley Pye Hayley C. Whitaker David Atkinson Shonit Punwani Daniel C. Alexander Eleftheria Panagiotaki Joint estimation of relaxation and diffusion tissue parameters for prostate cancer with relaxation-VERDICT MRI Scientific Reports |
| title | Joint estimation of relaxation and diffusion tissue parameters for prostate cancer with relaxation-VERDICT MRI |
| title_full | Joint estimation of relaxation and diffusion tissue parameters for prostate cancer with relaxation-VERDICT MRI |
| title_fullStr | Joint estimation of relaxation and diffusion tissue parameters for prostate cancer with relaxation-VERDICT MRI |
| title_full_unstemmed | Joint estimation of relaxation and diffusion tissue parameters for prostate cancer with relaxation-VERDICT MRI |
| title_short | Joint estimation of relaxation and diffusion tissue parameters for prostate cancer with relaxation-VERDICT MRI |
| title_sort | joint estimation of relaxation and diffusion tissue parameters for prostate cancer with relaxation verdict mri |
| url | https://doi.org/10.1038/s41598-023-30182-1 |
| work_keys_str_mv | AT marcopalombo jointestimationofrelaxationanddiffusiontissueparametersforprostatecancerwithrelaxationverdictmri AT vanyavalindria jointestimationofrelaxationanddiffusiontissueparametersforprostatecancerwithrelaxationverdictmri AT saurabhsingh jointestimationofrelaxationanddiffusiontissueparametersforprostatecancerwithrelaxationverdictmri AT elenichiou jointestimationofrelaxationanddiffusiontissueparametersforprostatecancerwithrelaxationverdictmri AT francescogiganti jointestimationofrelaxationanddiffusiontissueparametersforprostatecancerwithrelaxationverdictmri AT hayleypye jointestimationofrelaxationanddiffusiontissueparametersforprostatecancerwithrelaxationverdictmri AT hayleycwhitaker jointestimationofrelaxationanddiffusiontissueparametersforprostatecancerwithrelaxationverdictmri AT davidatkinson jointestimationofrelaxationanddiffusiontissueparametersforprostatecancerwithrelaxationverdictmri AT shonitpunwani jointestimationofrelaxationanddiffusiontissueparametersforprostatecancerwithrelaxationverdictmri AT danielcalexander jointestimationofrelaxationanddiffusiontissueparametersforprostatecancerwithrelaxationverdictmri AT eleftheriapanagiotaki jointestimationofrelaxationanddiffusiontissueparametersforprostatecancerwithrelaxationverdictmri |