Interactive registration of 2D histology and 3D CT data for assessment of radiofrequency ablation treatment

Seise, Matthias; Alhonnoro, Tuomas; Kolesnik, Marina

doi:10.4103/2153-3539.92036

Cited by 6 publications

(1 citation statement)

References 10 publications

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“…No standard for spatial registration of histological tissue sections to in vivo image data has emerged, but some methods have been proposed. 22,23 Most of them are in-house developments with, e.g., moulding of subcutaneous tumours or stereotactic assemblies and fiducial markers that preserve spatial orientation throughout the histological preparation. Various image registration techniques, such as rigid or affine and elastic registration have been proposed.…”

Section: Discussionmentioning

confidence: 99%

Multiparametric MR for non‐invasive evaluation of tumour tissue histological characteristics after radionuclide therapy

et al. 2019

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Early non‐invasive tumour therapy response assessment requires methods sensitive to biological and physiological tumour characteristics. The aim of this study was to find and evaluate magnetic resonance imaging (MRI) derived tumour tissue parameters that correlate with histological parameters and that reflect effects of radionuclide therapy. Mice bearing a subcutaneous human small‐intestine neuroendocrine tumour were i.v . injected with 177 Lu‐octreotate. MRI was performed (7 T Bruker Biospec) on different post‐therapy intervals (1 and 13 days) using T2‐weighted imaging, mapping of T2* and T1 relaxation time constants, as well as diffusion and dynamic contrast enhancement (DCE‐MRI) techniques. After MRI, animals were killed and tumours excised. Four differently stained histological sections of the most central imaged tumour plane were digitized, and segmentation techniques were used to produce maps reflecting fibrotic and vascular density, apoptosis, and proliferation. Histological maps were aligned with MRI‐derived parametric maps using landmark‐based registration. Correlations and predictive power were evaluated using linear mixed‐effects models and cross‐validation, respectively. Several MR parameters showed statistically significant correlations with histological parameters. In particular, three DCE‐MRI‐derived parameters reflecting capillary function additionally showed high predictive power regarding apoptosis (2/3) and proliferation (1/3). T1 could be used to predict vascular density, and perfusion fraction derived from diffusion MRI could predict fibrotic density, although with lower predictive power. This work demonstrates the potential to use multiparametric MRI to retrieve important information on the tumour microenvironment after radiotherapy. The non‐invasiveness of the method also allows longitudinal tumour tissue characterization. Further investigation is warranted to evaluate the parameters highlighted in this study longitudinally, in larger studies, and with additional histological methods.

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Section: Discussionmentioning

confidence: 99%

Multiparametric MR for non‐invasive evaluation of tumour tissue histological characteristics after radionuclide therapy

et al. 2019

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Radiofrequency ablation with four electrodes as a building block for matrix radiofrequency ablation: Ex vivo liver experiments and finite element method modelling. Influence of electric and activation mode on coagulation size and geometry

Mulier¹,

Possebon

Jiang³

et al. 2020

Surgical Oncology

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Radiofrequency ablation (RFA) is increasingly being used to treat unresectable liver tumors. Complete ablation of the tumor and a safety margin is necessary to prevent local recurrence.With current electrodes, size and shape of the ablation zone are highly variable leading to unsatisfactory local recurrence rates, especially for tumors > 3 cm. In order to improve Table 6: outcome of the ex vivo bovine liver experiments: comparison according to the number of electrodes activated at the same time.

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Automatic deformable registration of histological slides to μCT volume data

Chicherova

Hieber

Khimchenko

et al. 2018

Journal of Microscopy

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Localizing a histological section in the three-dimensional dataset of a different imaging modality is a challenging 2D-3D registration problem. In the literature, several approaches have been proposed to solve this problem; however, they cannot be considered as fully automatic. Recently, we developed an automatic algorithm that could successfully find the position of a histological section in a micro computed tomography (μCT) volume. For the majority of the datasets, the result of localization corresponded to the manual results. However, for some datasets, the matching μCT slice was off the ground-truth position. Furthermore, elastic distortions, due to histological preparation, could not be accounted for in this framework. In the current study, we introduce two optimization frameworks based on normalized mutual information, which enabled us to accurately register histology slides to volume data. The rigid approach allocated 81 % of histological sections with a median position error of 8.4 μm in jaw bone datasets, and the deformable approach improved registration by 33 μm with respect to the median distance error for four histological slides in the cerebellum dataset.

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Interactive registration of 2D histology and 3D CT data for assessment of radiofrequency ablation treatment

Cited by 6 publications

References 10 publications

Multiparametric MR for non‐invasive evaluation of tumour tissue histological characteristics after radionuclide therapy

Multiparametric MR for non‐invasive evaluation of tumour tissue histological characteristics after radionuclide therapy

Radiofrequency ablation with four electrodes as a building block for matrix radiofrequency ablation: Ex vivo liver experiments and finite element method modelling. Influence of electric and activation mode on coagulation size and geometry

Automatic deformable registration of histological slides to μCT volume data

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