Atherosclerotic Carotid Plaque Composition: A 3T and 7T MRI‐Histology Correlation Study

González, M. Roch; Foo, Sin Yee; Holmes, William M.; Stewart, William; Muir, Keith W.; Condon, Barrie; Welch, G. P.; Forbes, Kirsten

doi:10.1111/jon.12332

Cited by 14 publications

(11 citation statements)

References 40 publications

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“…We were able to achieve good visual agreement between histology and high-resolution MRI in all 12 plaques, which is similar to what has been shown in other studies [ [12] , [13] , [14] , [15] , [16] ].…”

Section: Discussionsupporting

confidence: 89%

Classifications of atherosclerotic plaque components with T1 and T2* mapping in 11.7 T MRI

Truong

Lennartsson

Bibic

et al. 2021

European Journal of Radiology Open

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Section: Discussionsupporting

confidence: 89%

Classifications of atherosclerotic plaque components with T1 and T2* mapping in 11.7 T MRI

Truong

Lennartsson

Bibic

et al. 2021

European Journal of Radiology Open

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“…Slice-to-slice approaches seem to be favoured for the visual control they allow. However, in most of the works the problem is only partly stated and adressed (Harkins et al, 2015;Kilsdonk et al, 2016;Hammelrath et al, 2016): Lopez Gonzalez et al (2016) performed linear registrations between ex vivo MR slices and histological images, and these were then visually matched to the closest (in vivo) 3T MR slice. Harteveld et al (2016) and Van Der Kolk et al (2015) manually matched histological sections to their corresponding MR planes using the marked locations from fiducials in the MR images, ink markings in the histologic sections, and gross morphologic features.…”

Section: Slice-to-slice Approaches (2d-2d)mentioning

confidence: 99%

A Survey of Methods for 3D Histology Reconstruction

Pichat

Iglesias

Yousry³

et al. 2018

Medical Image Analysis

170

179

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Histology permits the observation of otherwise invisible structures of the internal topography of a specimen. Although it enables the investigation of tissues at a cellular level, it is invasive and breaks topology due to cutting. Three-dimensional (3D) reconstruction was thus introduced to overcome the limitations of single-section studies in a dimensional scope. 3D reconstruction finds its roots in embryology, where it enabled the visualisation of spatial relationships of developing systems and organs, and extended to biomedicine, where the observation of individual, stained sections provided only partial understanding of normal and abnormal tissues. However, despite bringing visual awareness, recovering realistic reconstructions is elusive without prior knowledge about the tissue shape. 3D medical imaging made such structural ground truths available. In addition, combining non-invasive imaging with histology unveiled invaluable opportunities to relate macroscopic information to the underlying microscopic properties of tissues through the establishment of spatial correspondences; image registration is one technique that permits the automation of such a process and we describe reconstruction methods that rely on it. It is thereby possible to recover the original topology of histology and lost relationships, gain insight into what affects the signals used to construct medical images (and characterise them), or build high resolution anatomical atlases. This paper reviews almost three decades of methods for 3D histology reconstruction from serial sections, used in the study of many different types of tissue. We first summarise the process that produces digitised sections from a tissue specimen in order to understand the peculiarity of the data, the associated artefacts and some possible ways to minimise them. We then describe methods for 3D histology reconstruction with and without the help of 3D medical imaging, along with methods of validation and some applications. We finally attempt to identify the trends and challenges that the field is facing, many of which are derived from the cross-disciplinary nature of the problem as it involves the collaboration between physicists, histolopathologists, computer scientists and physicians.

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“…However, we believe, by means of a direct comparison between 40 MR images and histology sections, our results should be representative and convincing. Fourth, the measured areas of plaque components could not be validated by histology because the fixation and embedding could cause volume changes and tissue distortion of the plaque . Fifth, we did not compare MATCH with other new sequences such as 3D MPRAGE and simultaneous noncontrast angiography and intraplaque hemorrhage (SNAP), which seem promising in the detection of IPH because of the restricted scan time …”

Section: Discussionmentioning

confidence: 99%

Comparison study between multicontrast atherosclerosis characterization (MATCH) and conventional multicontrast MRI of carotid plaque with histology validation

Dai

Lin

et al. 2016

Magnetic Resonance Imaging

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Atherosclerotic Carotid Plaque Composition: A 3T and 7T MRI‐Histology Correlation Study

Abstract: Background and Purpose

Cited by 14 publications

References 40 publications

Classifications of atherosclerotic plaque components with T1 and T2* mapping in 11.7 T MRI

Classifications of atherosclerotic plaque components with T1 and T2* mapping in 11.7 T MRI

A Survey of Methods for 3D Histology Reconstruction

Comparison study between multicontrast atherosclerosis characterization (MATCH) and conventional multicontrast MRI of carotid plaque with histology validation

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