scholarly journals The Two-dimensional and Three-dimensional T2 Weighted Imaging-based Radiomic Signatures for the Preoperative Discrimination of Ovarian Borderline Tumors and Epithelial Cancer.

2020 ◽  
Author(s):  
Xuefen Liu ◽  
Tianping Wang ◽  
Guofu Zhang ◽  
Keqin Hua ◽  
Shaofeng Duan ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Operator Method ◽  
3D Segmentation ◽  
Borderline Tumors ◽  
Statistical Level ◽  
Highly Correlated ◽  
Selection Operator ◽  
2D And 3D ◽  
Testing Group ◽  
Segmentation Models

Abstract Background: Accurate discrimination between ovarian borderline tumors (BOTs) and malignancies with imaging play an important role in management.Methods: A total of 95 patients with pathologically proven ovarian BOTs and 101 patients with malignancies were retrospectively included in this study. We evaluated the diagnostic performance of the signatures derived from T2WI-based radiomics in their ability to differentiate between BOTs and malignancies and compared the performance differences in the 2D and 3D segmentation models. The least absolute shrinkage and selection operator method (LASSO) was used for radiomics feature selection and machine learning processing.Results: The radiomics score between BOTs and malignancies in four types of selected T2WI-based radiomics models differed significantly at the statistical level (p < 0.0001). For the classification between BOTs and malignant masses, the 2D and 3D coronal T2WI-based radiomics models yielded accuracy values of 0.79 and 0.83 in the testing group, respectively; the 2D and 3D sagittal fat-suppressed (fs) T2WI-based radiomics models yielded an accuracy of 0.78 and 0.99, respectively.Conclusion: Our results suggest that T2WI-based radiomic features were highly correlated with ovarian tumor subtype classification. 3D-sagittal MRI radiomics features may help clinicians differentiate ovarian BOTs from malignancies with high accuracy (ACC).

scholarly journals The Two-dimensional and Three-dimensional T2 Weighted Imaging-based Radiomic Signatures Selected for the Preoperative Discrimination of Ovarian Borderline Tumors and Epithelial Cancer.

2021 ◽  
Author(s):  
Xuefen Liu ◽  
Tianping Wang ◽  
Guofu Zhang ◽  
Keqin Hua ◽  
Hua Jiang ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Operator Method ◽  
Two Dimensional ◽  
Borderline Tumors ◽  
Segmentation Methods ◽  
Highly Correlated ◽  
Selection Operator ◽  
2D And 3D ◽  
Testing Group ◽  
Segmentation Models

Abstract Background: Accurate discrimination between ovarian borderline tumors (BOTs) and malignancies with imaging play an important role in management.Purpose: To evaluate the ability of T2-weighted imaging (T2WI)-based radiomics to discriminate ovarian borderline tumors (BOTs) from malignancies based on two-dimensional (2D) and three-dimensional (3D) lesion segmentation methods.Methods: A total of 95 patients with pathologically proven ovarian BOTs and 101 patients with malignancies were retrospectively included in this study. We evaluated the diagnostic performance of the signatures derived from T2WI-based radiomics in their ability to differentiate between BOTs and malignancies and compared the performance differences in the 2D and 3D segmentation models. The least absolute shrinkage and selection operator method (LASSO) was used for radiomics feature selection and machine learning processing.Results: The radiomics score between BOTs and malignancies in four types of selected T2WI-based radiomics models differed significantly at the statistical level (p < 0.0001). For the classification between BOTs and malignant masses, the 2D and 3D coronal T2WI-based radiomics models yielded accuracy values of 0.79 and 0.83 in the testing group, respectively; the 2D and 3D sagittal fat-suppressed (fs) T2WI-based radiomics models yielded an accuracy of 0.78 and 0.99, respectively.Conclusion: Our results suggest that T2WI-based radiomic features were highly correlated with ovarian tumor subtype classification. 3D-sagittal MRI radiomics features may help clinicians differentiate ovarian BOTs from malignancies with high accuracy (ACC).

scholarly journals Multidimensional and Multiresolution Ensemble Networks for Brain Tumor Segmentation

2019 ◽  
Author(s):  
Gowtham Krishnan Murugesan ◽  
Sahil Nalawade ◽  
Chandan Ganesh ◽  
Ben Wagner ◽  
Fang F. Yu ◽  
...  
Keyword(s):  
Brain Tumor ◽  
Learning Algorithm ◽  
Validation Dataset ◽  
Tumor Segmentation ◽  
Mr Images ◽  
3D Segmentation ◽  
Brain Tumor Segmentation ◽  
Robust Segmentation ◽  
2D And 3D ◽  
Segmentation Models

AbstractIn this work, we developed multiple 2D and 3D segmentation models with multiresolution input to segment brain tumor components, and then ensembled them to obtain robust segmentation maps. This reduced overfitting and resulted in a more generalized model. Multiparametric MR images of 335 subjects from BRATS 2019 challenge were used for training the models. Further, we tested a classical machine learning algorithm (xgboost) with features extracted from the segmentation maps to classify subject survival range. Preliminary results on the BRATS 2019 validation dataset demonstrasted this method can achieve excellent performance with DICE scores of 0.898, 0.784, 0.779 for whole tumor, tumor core and enhancing tumor respectively and accuracy 34.5 % for survuval prediction.

scholarly journals Comparison of Two-Dimensional- and Three-Dimensional-Based U-Net Architectures for Brain Tissue Classification in One-Dimensional Brain CT

2022 ◽  
Vol 15 ◽  
Author(s):  
Meera Srikrishna ◽  
Rolf A. Heckemann ◽  
Joana B. Pereira ◽  
Giovanni Volpe ◽  
Anna Zettergren ◽  
...  
Keyword(s):  
Deep Learning ◽  
Brain Tissue ◽  
Three Dimensional ◽  
Two Dimensional ◽  
3D Segmentation ◽  
Tissue Classification ◽  
Tissue Segmentation ◽  
One Dimensional ◽  
Ct Brain ◽  
2D And 3D

Brain tissue segmentation plays a crucial role in feature extraction, volumetric quantification, and morphometric analysis of brain scans. For the assessment of brain structure and integrity, CT is a non-invasive, cheaper, faster, and more widely available modality than MRI. However, the clinical application of CT is mostly limited to the visual assessment of brain integrity and exclusion of copathologies. We have previously developed two-dimensional (2D) deep learning-based segmentation networks that successfully classified brain tissue in head CT. Recently, deep learning-based MRI segmentation models successfully use patch-based three-dimensional (3D) segmentation networks. In this study, we aimed to develop patch-based 3D segmentation networks for CT brain tissue classification. Furthermore, we aimed to compare the performance of 2D- and 3D-based segmentation networks to perform brain tissue classification in anisotropic CT scans. For this purpose, we developed 2D and 3D U-Net-based deep learning models that were trained and validated on MR-derived segmentations from scans of 744 participants of the Gothenburg H70 Cohort with both CT and T1-weighted MRI scans acquired timely close to each other. Segmentation performance of both 2D and 3D models was evaluated on 234 unseen datasets using measures of distance, spatial similarity, and tissue volume. Single-task slice-wise processed 2D U-Nets performed better than multitask patch-based 3D U-Nets in CT brain tissue classification. These findings provide support to the use of 2D U-Nets to segment brain tissue in one-dimensional (1D) CT. This could increase the application of CT to detect brain abnormalities in clinical settings.

scholarly journals Homogeneous 2D and 3D alignment of cardiomyocyte in dilated cardiomyopathy revealed by intravital heart imaging

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kiyoshi Masuyama ◽  
Tomoaki Higo ◽  
Jong-Kook Lee ◽  
Ryohei Matsuura ◽  
Ian Jones ◽  
...  
Keyword(s):  
Heart Failure ◽  
Dilated Cardiomyopathy ◽  
Cardiac Dysfunction ◽  
Three Dimensional ◽  
Single Layer ◽  
Specific Pattern ◽  
Two Dimensional ◽  
Heart Imaging ◽  
Novel Method ◽  
2D And 3D

AbstractIn contrast to hypertrophic cardiomyopathy, there has been reported no specific pattern of cardiomyocyte array in dilated cardiomyopathy (DCM), partially because lack of alignment assessment in a three-dimensional (3D) manner. Here we have established a novel method to evaluate cardiomyocyte alignment in 3D using intravital heart imaging and demonstrated homogeneous alignment in DCM mice. Whilst cardiomyocytes of control mice changed their alignment by every layer in 3D and position twistedly even in a single layer, termed myocyte twist, cardiomyocytes of DCM mice aligned homogeneously both in two-dimensional (2D) and in 3D and lost myocyte twist. Manipulation of cultured cardiomyocyte toward homogeneously aligned increased their contractility, suggesting that homogeneous alignment in DCM mice is due to a sort of alignment remodelling as a way to compensate cardiac dysfunction. Our findings provide the first intravital evidence of cardiomyocyte alignment and will bring new insights into understanding the mechanism of heart failure.

scholarly journals Do 3D Face Images Capture Cues of Strength, Weight, and Height Better than 2D Face Images do?

2021 ◽  
Vol 7 (3) ◽  
pp. 209-219
Author(s):  
Iris J Holzleitner ◽  
Alex L Jones ◽  
Kieran J O’Shea ◽  
Rachel Cassar ◽  
Vanessa Fasolt ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Physical Characteristics ◽  
Two Dimensional ◽  
3D Images ◽  
3D Face ◽  
Face Images ◽  
Similar Accuracy ◽  
2D And 3D ◽  
2D Images ◽  
Better Than

Abstract Objectives A large literature exists investigating the extent to which physical characteristics (e.g., strength, weight, and height) can be accurately assessed from face images. While most of these studies have employed two-dimensional (2D) face images as stimuli, some recent studies have used three-dimensional (3D) face images because they may contain cues not visible in 2D face images. As equipment required for 3D face images is considerably more expensive than that required for 2D face images, we here investigated how perceptual ratings of physical characteristics from 2D and 3D face images compare. Methods We tested whether 3D face images capture cues of strength, weight, and height better than 2D face images do by directly comparing the accuracy of strength, weight, and height ratings of 182 2D and 3D face images taken simultaneously. Strength, height and weight were rated by 66, 59 and 52 raters respectively, who viewed both 2D and 3D images. Results In line with previous studies, we found that weight and height can be judged somewhat accurately from faces; contrary to previous research, we found that people were relatively inaccurate at assessing strength. We found no evidence that physical characteristics could be judged more accurately from 3D than 2D images. Conclusion Our results suggest physical characteristics are perceived with similar accuracy from 2D and 3D face images. They also suggest that the substantial costs associated with collecting 3D face scans may not be justified for research on the accuracy of facial judgments of physical characteristics.

Extracellular vesicles from three dimensional culture of human placental mesenchymal stem cells ameliorated renal ischemia/reperfusion injury

2021 ◽  
pp. 039139882098680
Author(s):  
Xuefeng Zhang ◽  
Nan Wang ◽  
Yuhua Huang ◽  
Yan Li ◽  
Gang Li ◽  
...  
Keyword(s):  
Stem Cells ◽  
Mesenchymal Stem Cells ◽  
Extracellular Vesicles ◽  
Therapeutic Potential ◽  
Expression Profiles ◽  
Ischemia Reperfusion ◽  
Three Dimensional ◽  
3D Culture ◽  
Placental Mesenchymal Stem Cells ◽  
2D And 3D

Background: Three-dimensional (3D) culture has been reported to increase the therapeutic potential of mesenchymal stem cells (MSCs). The present study assessed the therapeutic efficacy of extracellular vesicles (EVs) from 3D cultures of human placental MSCs (hPMSCs) for acute kidney injury (AKI). Methods: The supernatants from monolayer culture (2D) and 3D culture of hPMSCs were ultra-centrifuged for EVs isolation. C57BL/6 male mice were submitted to 45 min bilateral ischemia of kidney, followed by renal intra-capsular administration of EVs within a 72 h reperfusion period. Histological, immunohistochemical, and ELISA analyses of kidney samples were performed to evaluate cell death and inflammation. Kidney function was evaluated by measuring serum creatinine and urea nitrogen. The miRNA expression profiles of EVs from 2D and 3D culture of hPMSCs were evaluated using miRNA microarray analysis. Results: The 3D culture of hPMSCs formed spheroids with different diameters depending on the cell density seeded. The hPMSCs produced significantly more EVs in 3D culture than in 2D culture. More importantly, injection of EVs from 3D culture of hPMSCs into mouse kidney with ischemia-reperfusion (I/R)-AKI was more beneficial in protecting from progression of I/R than those from 2D culture. The EVs from 3D culture of hPMSCs were more efficient against apoptosis and inflammation than those from 2D culture, which resulted in a reduction in tissue damage and amelioration of renal function. MicroRNA profiling analysis revealed that a set of microRNAs were significantly changed in EVs from 3D culture of hPMSCs, especially miR-93-5p. Conclusion: The EVs from 3D culture of hPMSCs have therapeutic potential for I/R-AKI.

scholarly journals Value of Three-Dimensional Digital Subtraction Angiography for Detection and Classification of Intracranial Aneurysm Remnants After Clipping

2021 ◽  
Author(s):  
Serge Marbacher ◽  
Matthias Halter ◽  
Deborah R Vogt ◽  
Jenny C Kienzler ◽  
Christian T J Magyar ◽  
...  
Keyword(s):  
Intracranial Aneurysm ◽  
Digital Subtraction Angiography ◽  
Diagnostic Yield ◽  
Three Dimensional ◽  
P Value ◽  
Digital Subtraction ◽  
Patient Demographics ◽  
Included Patient ◽  
2D And 3D

Abstract BACKGROUND The current gold standard for evaluation of the surgical result after intracranial aneurysm (IA) clipping is two-dimensional (2D) digital subtraction angiography (DSA). While there is growing evidence that postoperative 3D-DSA is superior to 2D-DSA, there is a lack of data on intraoperative comparison. OBJECTIVE To compare the diagnostic yield of detection of IA remnants in intra- and postoperative 3D-DSA, categorize the remnants based on 3D-DSA findings, and examine associations between missed 2D-DSA remnants and IA characteristics. METHODS We evaluated 232 clipped IAs that were examined with intraoperative or postoperative 3D-DSA. Variables analyzed included patient demographics, IA and remnant distinguishing characteristics, and 2D- and 3D-DSA findings. Maximal IA remnant size detected by 3D-DSA was measured using a 3-point scale of 2-mm increments. RESULTS Although 3D-DSA detected all clipped IA remnants, 2D-DSA missed 30.4% (7 of 23) and 38.9% (14 of 36) clipped IA remnants in intraoperative and postoperative imaging, respectively (95% CI: 30 [ 12, 49] %; P-value .023 and 39 [23, 55] %; P-value = &lt;.001), and more often missed grade 1 (&lt; 2 mm) clipped remnants (odds ratio [95% CI]: 4.3 [1.6, 12.7], P-value .005). CONCLUSION Compared with 2D-DSA, 3D-DSA achieves a better diagnostic yield in the evaluation of clipped IA. Our proposed method to grade 3D-DSA remnants proved to be simple and practical. Especially small IA remnants have a high risk to be missed in 2D-DSA. We advocate routine use of either intraoperative or postoperative 3D-DSA as a baseline for lifelong follow-up of clipped IA.

Two-dimensional-Wilkins and real-time transesophageal three-dimensional scoring systems: Which one is preferred to mitral valve morphological assessment?

2021 ◽  
pp. 021849232110304
Author(s):  
Mehrnoush Toufan ◽  
Zahra Jabbary ◽  
Naser Khezerlou aghdam
Keyword(s):  
Mitral Valve ◽  
Transthoracic Echocardiography ◽  
Scoring System ◽  
Three Dimensional ◽  
Scoring Systems ◽  
Two Dimensional ◽  
Mitral Valve Area ◽  
2D And 3D ◽  
Morphological Assessment ◽  
Valve Area

Background To quantify valvular morphological assessment, some two-dimensional (2D) and three-dimensional (3D) scoring systems have been developed to target the patients for balloon mitral valvuloplasty; however, each scoring system has some potential limitations. To achieve the best scoring system with the most features and the least restrictions, it is necessary to check the degree of overlap of these systems. Also the factors related to the accuracy of these systems should be studied. We aimed to determine the correlation between the 2D Wilkins and real-time transesophageal three-dimensional (RT3D-TEE) scoring systems. Methods This cross-sectional study was performed on 156 patients with moderate to severe mitral stenosis who were candidates for percutaneous balloon valvuloplasty. To morphologic assessment of mitral valve, patients were examined by 2D-transthoracic echocardiography and RT3D-TEE techniques on the same day. Results A strong association was found between total Wilkins and total RT3D-TEE scores (r = 0.809, p < 0.001). The mean mitral valve area assessed by the 2D and 3D was 1.07 ± 0.25 and 1.03 ± 0.26, respectively, indicating a mean difference of 0.037 cm2 (p = 0.001). We found a strong correlation between the values of mitral valve area assessed by 2D and 3D techniques (r = 0.846, p < 0.001). Conclusion There is a high correlation between the two scoring systems in terms of evaluating dominant morphological features. Partially, mitral valve area overestimation in the 2D-transthoracic echocardiography and its inability to assess commissural involvement as well as its dependence on patient age were exceptions in this study.

scholarly journals Extending In-Plane Impedance Measurements from 2D to 3D Cultures: Design Considerations

2021 ◽  
Vol 8 (1) ◽  
pp. 11
Author(s):  
Sorel E. De Leon ◽  
Lana Cleuren ◽  
Zay Yar Oo ◽  
Paul R. Stoddart ◽  
Sally L. McArthur
Keyword(s):  
Three Dimensional ◽  
3D Culture ◽  
Collagen Gel ◽  
Impedance Measurement ◽  
Impedance Spectrum ◽  
3D Models ◽  
Low Frequencies ◽  
3D Cell Cultures ◽  
3D Collagen ◽  
2D And 3D

Three-dimensional (3D) cell cultures have recently emerged as tools for biologically modelling the human body. As 3D models make their way into laboratories there is a need to develop characterisation techniques that are sensitive enough to monitor the cells in real time and without the need for chemical labels. Impedance spectroscopy has been shown to address both of these challenges, but there has been little research into the full impedance spectrum and how the different components of the system affect the impedance signal. Here we investigate the impedance of human fibroblast cells in 2D and 3D collagen gel cultures across a broad range of frequencies (10 Hz to 5 MHz) using a commercial well with in-plane electrodes. At low frequencies in both 2D and 3D models it was observed that protein adsorption influences the magnitude of the impedance for the cell-free samples. This effect was eliminated once cells were introduced to the systems. Cell proliferation could be monitored in 2D at intermediate frequencies (30 kHz). However, the in-plane electrodes were unable to detect any changes in the impedance at any frequency when the cells were cultured in the 3D collagen gel. The results suggest that in designing impedance measurement devices, both the nature and distribution of the cells within the 3D culture as well as the architecture of the electrodes are key variables.

scholarly journals Designed and biologically active protein lattices

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Shih-Ting Wang ◽  
Brian Minevich ◽  
Jianfang Liu ◽  
Honghu Zhang ◽  
Dmytro Nykypanchuk ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Biologically Active ◽  
Double Layers ◽  
Active Protein ◽  
Functional Protein ◽  
Protein Arrays ◽  
Iron Storage ◽  
Nanoscale Systems ◽  
Framework Design ◽  
2D And 3D

AbstractVersatile methods to organize proteins in space are required to enable complex biomaterials, engineered biomolecular scaffolds, cell-free biology, and hybrid nanoscale systems. Here, we demonstrate how the tailored encapsulation of proteins in DNA-based voxels can be combined with programmable assembly that directs these voxels into biologically functional protein arrays with prescribed and ordered two-dimensional (2D) and three-dimensional (3D) organizations. We apply the presented concept to ferritin, an iron storage protein, and its iron-free analog, apoferritin, in order to form single-layers, double-layers, as well as several types of 3D protein lattices. Our study demonstrates that internal voxel design and inter-voxel encoding can be effectively employed to create protein lattices with designed organization, as confirmed by in situ X-ray scattering and cryo-electron microscopy 3D imaging. The assembled protein arrays maintain structural stability and biological activity in environments relevant for protein functionality. The framework design of the arrays then allows small molecules to access the ferritins and their iron cores and convert them into apoferritin arrays through the release of iron ions. The presented study introduces a platform approach for creating bio-active protein-containing ordered nanomaterials with desired 2D and 3D organizations.

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