scholarly journals A Pipelined Tracer-Aware Approach for Lesion Segmentation in Breast DCE-MRI

2021 ◽  
Vol 7 (12) ◽  
pp. 276
Author(s):  
Antonio Galli ◽  
Stefano Marrone ◽  
Gabriele Piantadosi ◽  
Mario Sansone ◽  
Carlo Sansone
Keyword(s):  
Contrast Agent ◽  
Time Course ◽  
Data Augmentation ◽  
Lesion Segmentation ◽  
Dce Mri ◽  
Training Strategy ◽  
Contrast Enhanced ◽  
Correction Technique ◽  
Limited Effectiveness ◽  
Unbalanced Dataset

The recent spread of Deep Learning (DL) in medical imaging is pushing researchers to explore its suitability for lesion segmentation in Dynamic Contrast-Enhanced Magnetic-Resonance Imaging (DCE-MRI), a complementary imaging procedure increasingly used in breast-cancer analysis. Despite some promising proposed solutions, we argue that a “naive” use of DL may have limited effectiveness as the presence of a contrast agent results in the acquisition of multimodal 4D images requiring thorough processing before training a DL model. We thus propose a pipelined approach where each stage is intended to deal with or to leverage a peculiar characteristic of breast DCE-MRI data: the use of a breast-masking pre-processing to remove non-breast tissues; the use of Three-Time-Points (3TP) slices to effectively highlight contrast agent time course; the application of a motion-correction technique to deal with patient involuntary movements; the leverage of a modified U-Net architecture tailored on the problem; and the introduction of a new “Eras/Epochs” training strategy to handle the unbalanced dataset while performing a strong data augmentation. We compared our pipelined solution against some literature works. The results show that our approach outperforms the competitors by a large margin (+9.13% over our previous solution) while also showing a higher generalization ability.

scholarly journals Dynamic contrast enhanced MRI with clinical hepatospecific MRI contrast agents in pigs: initial experience

2020 ◽  
Author(s):  
Jeremy M.L. Hix ◽  
Christiane L. Mallett ◽  
Matthew Latourette ◽  
Kirk A. Munoz ◽  
Erik M. Shapiro
Keyword(s):  
Contrast Agent ◽  
Contrast Agents ◽  
Biomedical Imaging ◽  
Mri Contrast Agents ◽  
Signal Enhancement ◽  
Pig Liver ◽  
Mri Contrast ◽  
Dce Mri ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced

AbstractPigs are an important translational research model for biomedical imaging studies, and especially for modeling diseases of the liver. Dynamic contrast enhanced (DCE)-MRI is experimentally used to measure liver function in humans, but has never been characterized in pig liver. Here we performed DCE-MRI of pig liver following the delivery of two FDA approved hepato-specific MRI contrast agents, Gd-EOB-DTPA (Eovist) and Gd-BOPTA (Multihance), and the non-hepatospecific agent Magnevist, and optimized the anesthesia and animal handling protocol to acquire robust data. A single pig underwent 5 scanning sessions over six weeks, each time injected at clinical dosing either with Eovist (twice), Multihance (twice) or Magnevist (once). DCE-MRI was performed at 1.5T for 60 minutes. DCE-MRI showed rapid hepatic MRI signal enhancement following IV injection of Eovist or Multihance. Efflux of contrast agent from liver exhibited kinetics similar to that in humans, except for one hyperthermic animal where efflux was very fast. As expected, Magnevist was non-enhancing in the liver. The hepatic signal enhancement from Eovist matched that seen in humans and primates, while the hepatic signal enhancement from Multihance was different, similar to rodents and dogs, likely the result of differential hepatic organic anion transport polypeptides. This first experience with these agents in pigs provides valuable information on contrast agent dynamics in normal pig liver. Given the disparity in contrast agent uptake kinetics with humans for Multihance, Eovist should be used in porcine models for biomedical imaging. Proper animal health maintenance, especially temperature, seems essential for accurate and reproducible results.

scholarly journals Absolute Perfusion Measurements and Associated Iodinated Contrast Agent Time Course in Brain Metastasis: A Study for Contrast-Enhanced Radiotherapy

2014 ◽  
Vol 34 (4) ◽  
pp. 638-645 ◽  
Author(s):  
Layal Obeid ◽  
Pierre Deman ◽  
Alexandre Tessier ◽  
Jacques Balosso ◽  
François Estève ◽  
...  
Keyword(s):  
Brain Metastasis ◽  
Contrast Agent ◽  
Time Course ◽  
Cerebral Blood Volume ◽  
Absolute Amount ◽  
X Rays ◽  
Iodinated Contrast ◽  
Contrast Enhanced ◽  
Iodinated Contrast Agent ◽  
Perfusion Measurements

Contrast-enhanced radiotherapy is an innovative treatment that combines the selective accumulation of heavy elements in tumors with stereotactic irradiations using medium energy X-rays. The radiation dose enhancement depends on the absolute amount of iodine reached in the tumor and its time course. Quantitative, postinfusion iodine biodistribution and associated brain perfusion parameters were studied in human brain metastasis as key parameters for treatment feasibility and quality. Twelve patients received an intravenous bolus of iodinated contrast agent (CA) (40 mL, 4 mL/s), followed by a steady-state infusion (160 mL, 0.5 mL/s) to ensure stable intratumoral amounts of iodine during the treatment. Absolute iodine concentrations and quantitative perfusion maps were derived from 40 multislice dynamic computed tomography (CT) images of the brain. The postinfusion mean intratumoral iodine concentration (over 30 minutes) reached 1.94±0.12 mg/mL. Reasonable correlations were obtained between these concentrations and the permeability surface area product and the cerebral blood volume. To our knowledge, this is the first quantitative study of CA biodistribution versus time in brain metastasis. The study shows that suitable and stable amounts of iodine can be reached for contrast-enhanced radiotherapy. Moreover, the associated perfusion measurements provide useful information for the patient recruitment and management processes.

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 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.

scholarly journals The Use of Dynamic Contrast-Enhanced Magnetic Resonance Imaging for the Evaluation of Blood-Brain Barrier Disruption in Traumatic Brain Injury: What Is the Evidence?

2021 ◽  
Vol 11 (6) ◽  
pp. 775
Author(s):  
Sung-Suk Oh ◽  
Eun-Hee Lee ◽  
Jong-Hoon Kim ◽  
Young-Beom Seo ◽  
Yoo-Jin Choo ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Magnetic Resonance ◽  
Blood Brain Barrier ◽  
Brain Barrier ◽  
Resonance Imaging ◽  
Dce Mri ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced

(1) Background: Blood brain barrier (BBB) disruption following traumatic brain injury (TBI) results in a secondary injury by facilitating the entry of neurotoxins to the brain parenchyma without filtration. In the current paper, we aimed to review previous dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) studies to evaluate the occurrence of BBB disruption after TBI. (2) Methods: In electronic databases (PubMed, Scopus, Embase, and the Cochrane Library), we searched for the following keywords: dynamic contrast-enhanced OR DCE AND brain injury. We included studies in which BBB disruption was evaluated in patients with TBI using DCE-MRI. (3) Results: Four articles were included in this review. To assess BBB disruption, linear fit, Tofts, extended Tofts, or Patlak models were used. KTrans and ve were increased, and the values of vp were decreased in the cerebral cortex and predilection sites for diffusion axonal injury. These findings are indicative of BBB disruption following TBI. (4) Conclusions: Our analysis supports the possibility of utilizing DCE-MRI for the detection of BBB disruption following TBI.

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