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

Bailey, Colleen; Bourne, Roger; Siow, Bernard; Johnston, Edward; Appayya, Mrishta Brizmohun; Pye, Hayley; Heavey, Susan; Mertzanidou, Thomy; Whitaker, Hayley C.; Freeman, Alex; Patel, Dominic; Shaw, Greg L.; Sridhar, Ashwin; Hawkes, David J.; Punwani, Shonit; Alexander, Daniel C.; Panagiotaki, Eleftheria

doi:10.1002/nbm.4073

Cited by 28 publications

(38 citation statements)

References 36 publications

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“…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%

Higher‐order diffusion MRI characterization of mesorectal lymph nodes in rectal cancer

Ianuş

Santiago

Galzerano

et al. 2019

Magnetic Resonance in Med

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Purpose Mesorectal lymph node staging plays an important role in treatment decision making. Here, we explore the benefit of higher‐order diffusion MRI models accounting for non‐Gaussian diffusion effects to classify mesorectal lymph nodes both 1) ex vivo at ultrahigh field correlated with histology and 2) in vivo in a clinical scanner upon patient staging. Methods The preclinical investigation included 54 mesorectal lymph nodes, which were scanned at 16.4 T with an extensive diffusion MRI acquisition. Eight diffusion models were compared in terms of goodness of fit, lymph node classification ability, and histology correlation. In the clinical part of this study, 10 rectal cancer patients were scanned with diffusion MRI at 1.5 T, and 72 lymph nodes were analyzed with Apparent Diffusion Coefficient (ADC), Intravoxel Incoherent Motion (IVIM), Kurtosis, and IVIM‐Kurtosis. Results Compartment models including restricted and anisotropic diffusion improved the preclinical data fit, as well as the lymph node classification, compared to standard ADC. The comparison with histology revealed only moderate correlations, and the highest values were observed between diffusion anisotropy metrics and cell area fraction. In the clinical study, the diffusivity from IVIM‐Kurtosis was the only metric showing significant differences between benign (0.80 ± 0.30 μm2/ms) and malignant (1.02 ± 0.41 μm2/ms, P = .03) nodes. IVIM‐Kurtosis also yielded the largest area under the receiver operating characteristic curve (0.73) and significantly improved the node differentiation when added to the standard visual analysis by experts based on T2‐weighted imaging. Conclusion Higher‐order diffusion MRI models perform better than standard ADC and may be of added value for mesorectal lymph node classification in rectal cancer patients.

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Section: Introductionmentioning

confidence: 92%

Higher‐order diffusion MRI characterization of mesorectal lymph nodes in rectal cancer

Ianuş

Santiago

Galzerano

et al. 2019

Magnetic Resonance in Med

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“…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%

A multimodal computational pipeline for 3D histology of the human brain

Mancini

Casamitjana

Peter

et al. 2020

Sci Rep

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Ex vivo imaging enables analysis of the human brain at a level of detail that is not possible in vivo with MRI. In particular, histology can be used to study brain tissue at the microscopic level, using a wide array of different stains that highlight different microanatomical features. Complementing MRI with histology has important applications in ex vivo atlas building and in modeling the link between microstructure and macroscopic MR signal. However, histology requires sectioning tissue, hence distorting its 3D structure, particularly in larger human samples. Here, we present an open-source computational pipeline to produce 3D consistent histology reconstructions of the human brain. The pipeline relies on a volumetric MRI scan that serves as undistorted reference, and on an intermediate imaging modality (blockface photography) that bridges the gap between MRI and histology. We present results on 3D histology reconstruction of whole human hemispheres from two donors. Motivation. One of the major challenges in the quest to understand the human brain as a complex system is characterizing its multiscale organization. From a macroscopic anatomical perspective, the brain is subdivided into distinct structures and presents well-defined landmarks, for instance its gyri and sulci. At a much finer scale, neurons are interconnected to form complex circuits. These circuits give rise to features at coarser scales, e.g., the laminar organization of the cortex 1. Although these distinct levels of organization may seem separate, they are, in fact, deeply linked and mutually influential. One clear example is given by Alzheimer's disease, which can be described by the interactions between proteinopathy at the microscale and distributed, network-level disruptions at the macroscale 2. Understanding these multi-scale mechanisms requires a multi-scale map of the brain. However, the current concept of brain mapping is closely linked to the specific tool used to construct cartographic representations, and thus to the spatial scale of the tool. As a result, the different organizational principles can only be observed in a scale-specific fashion with dedicated tools 3. Multi-scale imaging of the human brain is therefore necessarily multimodal, as different modalities are needed to study different scales. While a macroscopic anatomical picture of the brain is easily acquired non invasively or ex vivo with magnetic resonance imaging (MRI), finer characterization requires histological procedures and microscopy. Histology and MRI are highly complementary modalities: histology produces excellent contrast at the microscopic scale using dedicated stains that target different microanatomical or cytoarchitectural features, but it is a 2D modality that also inevitably introduces distortions in the tissue during blocking and sectioning. MRI does not yield microscopic resolution, but produces undistorted 3D volumes. Therefore, the combination of these two modalities offers a solution to the problem of imaging the human brain at high resolution in 3D.

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“…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%

Use of Magnetic Resonance Imaging and Biopsy Data to Guide Sampling Procedures for Prostate Cancer Biobanking

Heavey

Haider

Sridhar

et al. 2019

JoVE

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Previous methods for biobanking prostate tissue, following radical prostatectomy, generally involved random sampling. In order to increase efficiency, and enable a greater range of downstream applications, a more targeted method of sampling prostate tissue was developed. Here we use both magnetic resonance imaging (MRI) and biopsy data to target specific areas of the organ for sampling. The method involves use of a previously published prostate slicing device which removes a 5 mm transverse slice from a predetermined region of the prostate, followed by the removal of 6 mm punch biopsies from predetermined areas of this slice. These samples can be stored frozen or fixed for biobanking purposes, or used fresh immediately with 70% confidence of tumor content, as compared with 10% confidence from the random sampling approach. This enables the use of all standard downstream techniques such as genomics, proteomics or histological work, but also work that requires fresh tissue such as live tissue imaging or ex vivo culture.

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

Cited by 28 publications

References 36 publications

Higher‐order diffusion MRI characterization of mesorectal lymph nodes in rectal cancer

Higher‐order diffusion MRI characterization of mesorectal lymph nodes in rectal cancer

A multimodal computational pipeline for 3D histology of the human brain

Use of Magnetic Resonance Imaging and Biopsy Data to Guide Sampling Procedures for Prostate Cancer Biobanking

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