2019
DOI: 10.1002/nbm.4073
|View full text |Cite
|
Sign up to set email alerts
|

VERDICT MRI validation in fresh and fixed prostate specimens using patient‐specific moulds for histological and MR alignment

Abstract: The VERDICT framework for modelling diffusion MRI data aims to relate parameters from a biophysical model to histological features used for tumour grading in prostate cancer. Validation of the VERDICT model is necessary for clinical use. This study compared VERDICT parameters obtained ex vivo with histology in five specimens from radical prostatectomy. A patient‐specific 3D‐printed mould was used to investigate the effects of fixation on VERDICT parameters and to aid registration to histology. A rich diffusion… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3

Citation Types

2
36
0

Year Published

2019
2019
2024
2024

Publication Types

Select...
7
1

Relationship

3
5

Authors

Journals

citations
Cited by 28 publications
(38 citation statements)
references
References 36 publications
(53 reference statements)
2
36
0
Order By: Relevance
“…To further enhance the specificity of dMRI‐derived parameters to the underlying microstructure, recently proposed higher‐order dMRI techniques employ biophysical compartment models of various (assumed) tissue features to fit the dMRI measurements, usually acquired at multiple b ‐values and diffusion times. Such approaches showed enhanced ability over ADC to explain the diffusion measurements and differentiate between benign and malignant tumors in various cancer types such as xenograft colorectal tumors, prostate cancer, breast cancer, and gliomas . Moreover, the estimated dMRI parameters for restriction size and volume fraction correlated well with histology measurements .…”
Section: Introductionmentioning
confidence: 92%
“…To further enhance the specificity of dMRI‐derived parameters to the underlying microstructure, recently proposed higher‐order dMRI techniques employ biophysical compartment models of various (assumed) tissue features to fit the dMRI measurements, usually acquired at multiple b ‐values and diffusion times. Such approaches showed enhanced ability over ADC to explain the diffusion measurements and differentiate between benign and malignant tumors in various cancer types such as xenograft colorectal tumors, prostate cancer, breast cancer, and gliomas . Moreover, the estimated dMRI parameters for restriction size and volume fraction correlated well with histology measurements .…”
Section: Introductionmentioning
confidence: 92%
“…Related approaches in terms of target size include methods focused on small organs. Several studies have proposed combined MRI-histology approaches for the prostate 36 , 37 , lymphoidstructures 38 , mammary glands 39 , and kidneys 40 . Another comparable application is the study of small animal brains, in particular rodents 41 43 and small monkeys 44 , 45 .…”
Section: Introductionmentioning
confidence: 99%
“…This research need has led to the development of the PEOPLE (PatiEnt prOstate samPLes for rEsearch) method, and the results from the first 84 cases biobanked using PEOPLE were recently published 8 . A variation of this method has also been published with a three-dimensional (3D) printed slicing apparatus and patient-specific mold, in order to facilitate ex vivo MRI on pre-and post-fixation tissue 9,10 .…”
Section: Introductionmentioning
confidence: 99%