scholarly journals MULTIVARIATE MATHEMATICAL MORPHOLOGY FOR DCE-MRI IMAGE ANALYSIS IN ANGIOGENESIS STUDIES

2014 ◽  
Vol 34 (1) ◽  
pp. 1 ◽  
Author(s):  
Guillaume Noyel ◽  
Jesus Angulo ◽  
Dominique Jeulin ◽  
Daniel Balvay ◽  
Charles-André Cuenod
Keyword(s):  
Noise Reduction ◽  
Data Sets ◽  
Computer Aided Detection ◽  
Segmentation Method ◽  
Temporal Segmentation ◽  
Dce Mri ◽  
Contrast Enhanced ◽  
Key Points ◽  
Multivariate Images ◽  
Spatio Temporal

We propose a new computer aided detection framework for tumours acquired on DCE-MRI (Dynamic Contrast Enhanced Magnetic Resonance Imaging) series on small animals. To perform this approach, we consider DCE-MRI series as multivariate images. A full multivariate segmentation method based on dimensionality reduction, noise filtering, supervised classification and stochastic watershed is explained and tested on several data sets. The two main key-points introduced in this paper are noise reduction preserving contours and spatio temporal segmentation by stochastic watershed. Noise reduction is performed in a special way to select factorial axes of Factor Correspondence Analysis in order to preserves contours. Then a spatio-temporal approach based on stochastic watershed is used to segment tumours. The results obtained are in accordance with the diagnosis of the medical doctors.

Assessment of Kidney Function Using Dynamic Contrast Enhanced MRI Techniques

2010 ◽  
pp. 214-233
Author(s):  
Melih S. Aslan ◽  
Hossam Abd El Munim ◽  
Aly A. Farag ◽  
Mohamed Abou El-Ghar
Keyword(s):  
Kidney Function ◽  
Least Square ◽  
Renal Diseases ◽  
Support Vector ◽  
Data Sets ◽  
Dce Mri ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced ◽  
Vector Machines ◽  
Kidney Rejection

Graft failure of kidneys after transplantation is most often the consequence of the acute rejection. Hence, early detection of the kidney rejection is important for the treatment of renal diseases. In this chapter, authors introduce a new automatic approach to classify normal kidney function from kidney rejection using dynamic contrast enhanced magnetic resonance imaging (DCE-MRI). The kidney has three regions named the cortex, medulla, and pelvis. In their experiment, they use the medulla region because it has specific responses to DCE-MRI that are helpful to identify kidney rejection. In the authors’ process they segment the kidney using the level sets method. They then employ several classification methods such as the Euclidean distance, Mahalanobis distance, and least square support vector machines (LS-SVM). The authors’preliminary results are very encouraging and reproducibility of the results was achieved for 55 clinical data sets. The classification accuracy, diagnostic sensitivity, and diagnostic specificity are 84%, 75%, and 96%, respectively.

scholarly journals A Four-Dimensional Computational Model of Dynamic Contrast-Enhanced Magnetic Resonance Imaging Measurement of Subtle Blood-Brain Barrier Leakage

2020 ◽  
Author(s):  
Jose Bernal ◽  
Maria Valdés-Hernández ◽  
Javier Escudero ◽  
Anna Heye ◽  
Eleni Sakka ◽  
...  
Keyword(s):  
Computational Model ◽  
Blood Brain Barrier ◽  
Brain Barrier ◽  
Dce Mri ◽  
Temporal Effects ◽  
Dynamic Contrast Enhanced ◽  
Imaging Protocols ◽  
Contrast Enhanced ◽  
Spatio Temporal ◽  
The Impact

Dynamic contrast-enhanced MRI (DCE-MRI) is increasingly used to quantify and map the spatial distribution of blood-brain barrier (BBB) leakage in neurodegenerative disease, including cerebral small vessel disease and dementia. However, the subtle nature of leakage and resulting small signal changes make quantification challenging. While simplified one-dimensional simulations have probed the impact of noise, scanner drift, and model assumptions, the impact of spatio-temporal effects such as gross motion, k-space sampling and motion artefacts on parametric leakage maps has been overlooked. Moreover, evidence on which to base the design of imaging protocols is lacking due to practical difficulties and the lack of a reference method. To address these problems, we present an open-source computational model of the DCE-MRI acquisition process for generating four-dimensional Digital Reference Objects (DROs), using a high-resolution brain atlas and incorporating realistic patient motion, extra-cerebral signals, noise and k-space sampling. Simulations using the DROs demonstrated a dominant influence of spatio-temporal effects on both the visual appearance of parameter maps and on measured tissue leakage rates. The computational model permits a greater understanding of the sensitivity and limitations of subtle BBB leakage measurement and provides a non-invasive means of testing and optimising imaging protocols for future studies.

scholarly journals A Fully Automated Three-Stage Procedure for Spatio-Temporal Leaf Segmentation with Regard to the B-Spline-Based Phenotyping of Cucumber Plants

2020 ◽  
Vol 13 (1) ◽  
pp. 74
Author(s):  
Corinna Harmening ◽  
Jens-André Paffenholz
Keyword(s):  
Measurement Techniques ◽  
Point Clouds ◽  
Plant Phenotyping ◽  
Data Sets ◽  
Temporal Segmentation ◽  
B Spline ◽  
Crop Science ◽  
Spline Surfaces ◽  
Spatio Temporal ◽  
The Impact

Plant phenotyping deals with the metrological acquisition of plants in order to investigate the impact of environmental factors and a plant’s genotype on its appearance. Phenotyping methods that are used as standard in crop science are often invasive or even destructive. Due to the increase of automation within geodetic measurement systems and with the development of quasi-continuous measurement techniques, geodetic techniques are perfectly suitable for performing automated and non-invasive phenotyping and, hence, are an alternative to standard phenotyping methods. In this contribution, sequentially acquired point clouds of cucumber plants are used to determine the plants’ phenotypes in terms of their leaf areas. The focus of this contribution is on the spatio-temporal segmentation of the acquired point clouds, which automatically groups and tracks those sub point clouds that describe the same leaf. The application on example data sets reveals a successful segmentation of 93% of the leafs. Afterwards, the segmented leaves are approximated by means of B-spline surfaces, which provide the basis for the subsequent determination of the leaf areas. In order to validate the results, the determined leaf areas are compared to results obtained by means of standard methods used in crop science. The investigations reveal consistency of the results with maximal deviations in the determined leaf areas of up to 5%.

scholarly journals Perfusion in hand arthritis on dynamic contrast-enhanced computed tomography: a randomized prospective study using MRI as a standard of reference

2020 ◽  
Vol 50 (1) ◽  
pp. 59-68
Author(s):  
Sevtap Tugce Ulas ◽  
Kay Geert Hermann ◽  
Marcus R. Makowski ◽  
Robert Biesen ◽  
Fabian Proft ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Mean Transit Time ◽  
Region Of Interest ◽  
T Test ◽  
Dose Length Product ◽  
Suitable Alternative ◽  
Dce Mri ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced Ct ◽  
Contrast Enhanced

Abstract Objective To evaluate the performance of dynamic contrast-enhanced CT (DCE-CT) in detecting and quantitatively assessing perfusion parameters in patients with arthritis of the hand compared with dynamic contrast-enhanced MRI (DCE-MRI) as a standard of reference. Materials and methods In this IRB-approved randomized prospective single-centre study, 36 consecutive patients with suspected rheumatoid arthritis underwent DCE-CT (320-row, tube voltage 80 kVp, tube current 8.25 mAs) and DCE-MRI (1.5 T) of the hand. Perfusion maps were calculated separately for mean transit time (MTT), time to peak (TTP), relative blood volume (rBV), and relative blood flow (rBF) using four different decomposition techniques. Region of interest (ROI) analysis was performed in metacarpophalangeal joints II–V and in the wrist. Pairs of perfusion parameters in DCE-CT and DCE-MRI were compared using a two-tailed t test for paired samples and interpreted for effect size (Cohen’s d). According to the Rheumatoid Arthritis Magnetic Resonance Imaging Score (RAMRIS) scoring results, differentiation of synovitis-positive and synovitis-negative joints with both modalities was assessed with the independent t test. Results The two modalities yielded similar perfusion parameters. Identified differences had small effects (d 0.01–0.4). DCE-CT additionally differentiates inflamed and noninflamed joints based on rBF and rBV but tends to underestimate these parameters in severe inflammation. The total dose-length product (DLP) was 48 mGy*cm with an estimated effective dose of 0.038 mSv. Conclusion DCE-CT is a promising imaging technique in arthritis. In patients with a contraindication to MRI or when MRI is not available, DCE-CT is a suitable alternative to detect and assess arthritis.

scholarly journals Radiomic and Artificial Intelligence Analysis with Textural Metrics, Morphological and Dynamic Perfusion Features Extracted by Dynamic Contrast-Enhanced Magnetic Resonance Imaging in the Classification of Breast Lesions

2021 ◽  
Vol 11 (4) ◽  
pp. 1880
Author(s):  
Roberta Fusco ◽  
Adele Piccirillo ◽  
Mario Sansone ◽  
Vincenza Granata ◽  
Paolo Vallone ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Artificial Intelligence ◽  
Feature Selection ◽  
Resonance Imaging ◽  
Dynamic Features ◽  
Surgical Specimen ◽  
Dce Mri ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced ◽  
Malignant Lesions

Purpose: The aim of the study was to estimate the diagnostic accuracy of textural, morphological and dynamic features, extracted by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) images, by carrying out univariate and multivariate statistical analyses including artificial intelligence approaches. Methods: In total, 85 patients with known breast lesion were enrolled in this retrospective study according to regulations issued by the local Institutional Review Board. All patients underwent DCE-MRI examination. The reference standard was pathology from a surgical specimen for malignant lesions and pathology from a surgical specimen or fine needle aspiration cytology, core or Tru-Cut needle biopsy for benign lesions. In total, 91 samples of 85 patients were analyzed. Furthermore, 48 textural metrics, 15 morphological and 81 dynamic parameters were extracted by manually segmenting regions of interest. Statistical analyses including univariate and multivariate approaches were performed: non-parametric Wilcoxon–Mann–Whitney test; receiver operating characteristic (ROC), linear classifier (LDA), decision tree (DT), k-nearest neighbors (KNN), and support vector machine (SVM) were utilized. A balancing approach and feature selection methods were used. Results: The univariate analysis showed low accuracy and area under the curve (AUC) for all considered features. Instead, in the multivariate textural analysis, the best performance (accuracy (ACC) = 0.78; AUC = 0.78) was reached with all 48 metrics and an LDA trained with balanced data. The best performance (ACC = 0.75; AUC = 0.80) using morphological features was reached with an SVM trained with 10-fold cross-variation (CV) and balanced data (with adaptive synthetic (ADASYN) function) and a subset of five robust morphological features (circularity, rectangularity, sphericity, gleaning and surface). The best performance (ACC = 0.82; AUC = 0.83) using dynamic features was reached with a trained SVM and balanced data (with ADASYN function). Conclusion: Multivariate analyses using pattern recognition approaches, including all morphological, textural and dynamic features, optimized by adaptive synthetic sampling and feature selection operations obtained the best results and showed the best performance in the discrimination of benign and malignant lesions.

scholarly journals Spatio-temporal Segmentation Based Adaptive Compression of Dynamic Mesh Sequences

2020 ◽  
Vol 16 (1) ◽  
pp. 1-24
Author(s):  
Guoliang Luo ◽  
Zhigang Deng ◽  
Xin Zhao ◽  
Xiaogang Jin ◽  
Wei Zeng ◽  
...  
Keyword(s):  
Dynamic Mesh ◽  
Temporal Segmentation ◽  
Adaptive Compression ◽  
Spatio Temporal

scholarly journals Can DWI-MRI be an alternative to DCE-MRI in the diagnosis of troublesome breast lesions?

2021 ◽  
Vol 52 (1) ◽  
Author(s):  
Lamiaa Mohamed Bassam Hashem ◽  
Sherihan W. Y. Gareer ◽  
Aya Mohamed Bassam Hashem ◽  
Sherihan Fakhry ◽  
Yasmin Mounir Tohamey
Keyword(s):  
Problem Solver ◽  
Breast Lesions ◽  
Diffusion Weighted Mri ◽  
Resonance Imaging ◽  
Contrast Administration ◽  
Dce Mri ◽  
Water Diffusivity ◽  
Contrast Enhanced ◽  
Mri Study ◽  
Established Technique

Abstract Background Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has always been a problem solver in troublesome breast lesions. Despite its many advantages, the encountered low specificity results in unnecessary biopsies. Diffusion-weighted MRI (DW-MRI) is a well-established technique that helps in characterizing breast lesions according to their water diffusivity. So this work aimed to assess the diagnostic performance of DW-MRI in troublesome breast lesions and see if it can replace DCE-MRI study. Results In our prospective study, we included 86 patients with mammography and/or ultrasound-detected 90 probably benign or probably malignant (BIRADS 3 or 4) breast lesions. Among the studied cases, 49/90 lesions were benign, and 41/90 were malignant. Combined analysis of morphological and kinetic findings in DCE-MRI had achieved the highest sensitivity of 95.1%. DW-MRI alone was less sensitive (73.2%) yet more specific (83.7%) than DCE-MRI (77.6%). Diagnostic accuracy of DCE-MRI was higher (85.6%) as compared to DW-MRI which was (78.9%). Conclusion DCE-MRI is the cornerstone in the workup of troublesome breast lesions. DW-MRI should not be used as supplementary tool unless contrast administration is contraindicated. Combining both DCE-MRI and DW-MRI is the ultimate technique for better lesion evaluation.

scholarly journals Extended perfusion protocol for MS lesion quantification

Open Medicine ◽  
2020 ◽  
Vol 15 (1) ◽  
pp. 520-530
Author(s):  
Eleftherios Kontopodis ◽  
Kostas Marias ◽  
Georgios C. Manikis ◽  
Katerina Nikiforaki ◽  
Maria Venianaki ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Magnetic Resonance ◽  
Goodness Of Fit ◽  
Accurate Determination ◽  
Acquisition Time ◽  
Minimal Extension ◽  
Dce Mri ◽  
Contrast Enhanced ◽  
Demyelinating Lesions ◽  
Mri Protocol

AbstractThis study aims to examine a time-extended dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) protocol and report a comparative study with three different pharmacokinetic (PK) models, for accurate determination of subtle blood–brain barrier (BBB) disruption in patients with multiple sclerosis (MS). This time-extended DCE-MRI perfusion protocol, called Snaps, was applied on 24 active demyelinating lesions of 12 MS patients. Statistical analysis was performed for both protocols through three different PK models. The Snaps protocol achieved triple the window time of perfusion observation by extending the magnetic resonance acquisition time by less than 2 min on average for all patients. In addition, the statistical analysis in terms of adj-R2 goodness of fit demonstrated that the Snaps protocol outperformed the conventional DCE-MRI protocol by detecting 49% more pixels on average. The exclusive pixels identified from the Snaps protocol lie in the low ktrans range, potentially reflecting areas with subtle BBB disruption. Finally, the extended Tofts model was found to have the highest fitting accuracy for both analyzed protocols. The previously proposed time-extended DCE protocol, called Snaps, provides additional temporal perfusion information at the expense of a minimal extension of the conventional DCE acquisition time.

scholarly journals Dynamic contrast-enhanced magnetic resonance imaging for monitoring neovascularization during bone regeneration—a randomized in vivo study in rabbits

2021 ◽  
Author(s):  
L. A. R. Righesso ◽  
M. Terekhov ◽  
H. Götz ◽  
M. Ackermann ◽  
T. Emrich ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Bone Regeneration ◽  
Blood Perfusion ◽  
Autogenous Bone ◽  
Resonance Imaging ◽  
Dce Mri ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced

Abstract Objectives Micro-computed tomography (μ-CT) and histology, the current gold standard methods for assessing the formation of new bone and blood vessels, are invasive and/or destructive. With that in mind, a more conservative tool, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), was tested for its accuracy and reproducibility in monitoring neovascularization during bone regeneration. Additionally, the suitability of blood perfusion as a surrogate of the efficacy of osteoplastic materials was evaluated. Materials and methods Sixteen rabbits were used and equally divided into four groups, according to the time of euthanasia (2, 3, 4, and 6 weeks after surgery). The animals were submitted to two 8-mm craniotomies that were filled with blood or autogenous bone. Neovascularization was assessed in vivo through DCE-MRI, and bone regeneration, ex vivo, through μ-CT and histology. Results The defects could be consistently identified, and their blood perfusion measured through DCE-MRI, there being statistically significant differences within the blood clot group between 3 and 6 weeks (p = 0.029), and between the former and autogenous bone at six weeks (p = 0.017). Nonetheless, no significant correlations between DCE-MRI findings on neovascularization and μ-CT (r =−0.101, 95% CI [−0.445; 0.268]) or histology (r = 0.305, 95% CI [−0.133; 0.644]) findings on bone regeneration were observed. Conclusions These results support the hypothesis that DCE-MRI can be used to monitor neovascularization but contradict the premise that it could predict bone regeneration as well.

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