Automatic Segmentation of Eight Tissue Classes in Neonatal Brain MRI

Purpose

Volumetric measurements of neonatal brain tissues may be used as a biomarker for later neurodevelopmental outcome. We propose an automatic method for probabilistic brain segmentation in neonatal MRIs.

Materials and Methods

In an IRB-approved study axial T1- and T2-weighted MR images were acquired at term-equivalent age for a preterm cohort of 108 neonates. A method for automatic probabilistic segmentation of the images into eight cerebral tissue classes was developed: cortical and central grey matter, unmyelinated and myelinated white matter, cerebrospinal fluid in the ventricles and in the extra cerebral space, brainstem and cerebellum. Segmentation is based on supervised pixel classification using intensity values and spatial positions of the image voxels. The method was trained and evaluated using leave-one-out experiments on seven images, for which an expert had set a reference standard manually. Subsequently, the method was applied to the remaining 101 scans, and the resulting segmentations were evaluated visually by three experts. Finally, volumes of the eight segmented tissue classes were determined for each patient.

Results

The Dice similarity coefficients of the segmented tissue classes, except myelinated white matter, ranged from 0.75 to 0.92. Myelinated white matter was difficult to segment and the achieved Dice coefficient was 0.47. Visual analysis of the results demonstrated accurate segmentations of the eight tissue classes. The probabilistic segmentation method produced volumes that compared favorably with the reference standard.

Conclusion

The proposed method provides accurate segmentation of neonatal brain MR images into all given tissue classes, except myelinated white matter. This is the one of the first methods that distinguishes cerebrospinal fluid in the ventricles from cerebrospinal fluid in the extracerebral space. This method might be helpful in predicting neurodevelopmental outcome and useful for evaluating neuroprotective clinical trials in neonates.     

Line Detection and Texture Analysis for Automatic Nematode Identification

This paper is the second in a series studying procedures for estimating and calibrating features of nematodes from digital images. Two kinds of features were analyzed for recognition: those with a directional component and those with a textural component. Features that have a directional component (lateral field and annules) were preprocessed with classic algorithms and modified by directional filters. Features having texture (esophagus and intestine) were analyzed with vectors of measures to define them and the statistical technique CART (classification and regression trees) to explain the role that each measure plays in the identification and discrimination process.     

Diffusion MRI and Novel Texture Analysis in Osteosarcoma Xenotransplants Predicts Response to Anti-Checkpoint Therapy

Combinations of targeted drugs have been employed to treat sarcomas, however, response rates have not improved notably, therefore emphasizing the need for novel treatments. In addition, imaging approaches to assess therapeutic response is lacking, as currently measurable indices, such as volume and/or diameter, do not accurately correlate with changes in tumor biology. In this study, quantitative and profound analyses of magnetic resonance imaging (MRI) were developed to evaluate these as imaging biomarkers for MK1775 and Gem in an osteosarcoma xenotransplant model at early time-points following treatment. Notably, we showed that Gem and Gem+MK1775 groups had significantly inhibited tumor growth by day 4, which was presaged by elevations in mean ADC by 24 hours post treatment. Significant differences were also observed at later time points for the Gem+MK1775 combination and MK1775 therapy. ADC distribution and entropy (randomness of ADC values) were also elevated by 24 hours following therapy. Immunohistochemistry demonstrated that these treatment-related increases in ADC correlated with apoptosis and observed cell condensations (dense- and exploded bodies). These findings underline the role of ADC as a quantitative imaging biomarker for therapy-induced response and show promising clinical relevance in the sarcoma patient population.     

Multi-Parametric MRI and Texture Analysis to Visualize Spatial Histologic Heterogeneity and Tumor Extent in Glioblastoma

Background

Genetic profiling represents the future of neuro-oncology but suffers from inadequate biopsies in heterogeneous tumors like Glioblastoma (GBM). Contrast-enhanced MRI (CE-MRI) targets enhancing core (ENH) but yields adequate tumor in only ~60% of cases. Further, CE-MRI poorly localizes infiltrative tumor within surrounding non-enhancing parenchyma, or brain-around-tumor (BAT), despite the importance of characterizing this tumor segment, which universally recurs. In this study, we use multiple texture analysis and machine learning (ML) algorithms to analyze multi-parametric MRI, and produce new images indicating tumor-rich targets in GBM.

Methods

We recruited primary GBM patients undergoing image-guided biopsies and acquired pre-operative MRI: CE-MRI, Dynamic-Susceptibility-weighted-Contrast-enhanced-MRI, and Diffusion Tensor Imaging. Following image coregistration and region of interest placement at biopsy locations, we compared MRI metrics and regional texture with histologic diagnoses of high- vs low-tumor content (≥80% vs <80% tumor nuclei) for corresponding samples. In a training set, we used three texture analysis algorithms and three ML methods to identify MRI-texture features that optimized model accuracy to distinguish tumor content. We confirmed model accuracy in a separate validation set.

Results

We collected 82 biopsies from 18 GBMs throughout ENH and BAT. The MRI-based model achieved 85% cross-validated accuracy to diagnose high- vs low-tumor in the training set (60 biopsies, 11 patients). The model achieved 81.8% accuracy in the validation set (22 biopsies, 7 patients).

Conclusion

Multi-parametric MRI and texture analysis can help characterize and visualize GBM’s spatial histologic heterogeneity to identify regional tumor-rich biopsy targets.     

A Method for Detecting Visceral Malformations in Gelatin-Embedded Rat Fetuses Using an Automatic Slicing Apparatus

A method for observing whole rat fetal viscera embedded in gelatin using an automatic slicing apparatus is described. Fetuses were immersed in Bouin's solution. Part of the thoracic and abdominal skin of each fetus was removed, and fetuses were immersed consecutively in sodium bicarbonate 30% in 70% ethanol, gelatin 15% in water, gelatin 30% in water, then embedded in fresh 30% gelatin. The gelatin blocks containing the fetuses were immersed in 10% formalin. After fixation, the block was sliced into 200 μm serial transverse sections using a rotor-slicer at a rotation speed of 120 rpm and a cutting speed of 25 mm/sec. Complete slicing of a single fetus required about 20 min. The advantages of the method presented here include: complete fetal serial sections are produced, thin and uniform sections are obtained easily, viscera can be identified easily, and observation can be carried out at any time after slicing. The method presented can be used to detect whole fetal visceral malformations in developmental toxicity tests.     

Histogram Analysis of Gadoxetic Acid-Enhanced MRI for Quantitative Hepatic Fibrosis Measurement

Purpose

The diagnosis and monitoring of liver fibrosis is an important clinical issue; however, this is usually achieved by invasive methods such as biopsy. We aimed to determine whether histogram analysis of hepatobiliary phase images of gadoxetic acid-enhanced magnetic resonance imaging (MRI) can provide non-invasive quantitative measurement of liver fibrosis.

Methods

This retrospective study was approved by the institutional ethics committee, and a waiver of informed consent was obtained. Hepatobiliary phase images of preoperative gadoxetic acid-enhanced MRI studies of 105 patients (69 males, 36 females; age 56.1±12.2) with pathologically documented liver fibrosis grades were analyzed. Fibrosis staging was F0/F1/F2/F3/F4 (METAVIR system) for 11/20/13/15/46 patients, respectively. Four regions-of-interest (ROI, each about 2 cm²) were placed on predetermined locations of representative images. The measured signal intensity of pixels in each ROI was used to calculate corrected coefficient of variation (cCV), skewness, and kurtosis. An average value of each parameter was calculated for comparison. Statistical analysis was performed by ANOVA, receiver operating characteristic (ROC) curve analysis, and linear regression.

Results

The cCV showed statistically significant differences among pathological fibrosis grades (P<0.001) whereas skewness and kurtosis did not. Univariable linear regression analysis suggested cCV to be a meaningful parameter in predicting the fibrosis grade (P<0.001, β = 0.40 and standard error  = 0.06). For discriminating F0-3 from F4, the area under ROC score was 0.857, standard deviation 0.036, 95% confidence interval 0.785–0.928.

Conclusion

Histogram analysis of hepatobiliary phase images of gadoxetic acid-enhanced MRI can provide non-invasive quantitative measurements of hepatic fibrosis.     

The Potential Value of Preoperative MRI Texture and Shape Analysis in Grading Meningiomas: A Preliminary Investigation

OBJECT: Preoperative knowledge of meningioma grade is essential for planning treatment and surgery. The purpose of this study was to investigate the diagnostic value of MRI texture and shape analysis in grading meningiomas. METHODS: A surgical database was reviewed to identify meningioma patients who had undergone tumor resection between January 2015 and December 2016. Preoperative MR images were retrieved and analyzed. Texture and shape analysis was conducted to quantitatively evaluate tumor heterogeneity and morphology. Three machine learning classifiers were trained with these features to build classification models. The performance of the features and classification models was assessed. RESULTS: A total of 131 patients were included in this study: 21 with high-grade meningiomas and 110 with low-grade meningiomas. Three texture features were selected: Horzl_RLNonUni, S(2,2)SumOfSqs, and WavEnHL_s-3; three shape features were selected: GeoFv, GeoW4, and GeoW5b. The Mann–Whitney test indicated that all six features were significantly different between high-grade and low-grade meningiomas. AUC values were generally greater than 0.50 (range, 0.73 to 0.88). Sensitivities and specificities ranged from 47.62% to 90.48% and 69.09% to 96.36%, respectively. Among the nine classification models obtained, the one built by training the SVM classifier with all six features achieved the best performance, with a sensitivity, specificity, diagnostic accuracy, and AUC of 0.86, 0.87, 0.87, and 0.87, respectively. CONCLUSIONS: Texture and shape analysis, especially when combined with a SVM classifier, can provide satisfactory performance in the preoperative determination of meningioma grade and is thus potentially useful for clinical application.     

Abnormal Resting-State Connectivity at Functional MRI in Women with Premenstrual Syndrome

Objectives

Premenstrual syndrome (PMS) refers to a series of cycling and relapsing physical, emotion and behavior syndromes that occur in the luteal phase and resolve soon after the onset of menses. Although PMS is widely recognized, its neural mechanism is still unclear.

Design

To address this question, we measured brain activity for women with PMS and women without PMS (control group) using resting-state functional magnetic resonance imaging (rs-fMRI). In addition, the participants should complete the emotion scales (Beck Anxiety Inventory, BAI; Beck Depression Inventory, BDI, before the scanning) as well as the stress perception scale (Visual analog scale for stress, VAS, before and after the scanning).

Results

The results showed that compared with the control group, the PMS group had decreased connectivity in the middle frontal gyrus (MFG) and theparahippocampalgyrus (PHG), as well as increased connectivity in the left medial/superior temporal gyri (MTG/STG) and precentralgyrus within the default mode network (DMN); in addition, the PMS group had higher anxiety and depression scale scores, together with lower stress perception scores. Finally, there were significantly positive correlations between the stress perception scores and functional connectivity in the MFG and cuneus. The BDI scores in the PMS group were correlated negatively with the functional connectivity in the MFG and precuneus and correlated positively with the functional connectivity in the MTG.

Conclusion

These findings suggest that compared with normal women, women with PMS displayed abnormal stress sensitivity, which was reflected in the decreased and increased functional connectivity within the DMN, blunted stress perception and higher depression.     

Chromatin Texture Analysis in Living Cells

In recent years, there has been an increasing interest in applications of fluorescence measurements to studies on many physiological mechanisms in living cells. However, few studies have taken advantage of DNA quantification by fluorometry for dynamic assessment of chromatin organization. This type of approach involves both optimal conditions for DNA staining and the use of image cytometry. In this context, this report describes the application of an internal grey-level segmentation method for the assessment of real time modifications of chromatin organization in living cells. These developments are based on a specific, stoichiometric method for nuclear DNA content measurement. Preliminary data obtained from Hela cells suggests the possibility of following variations of nuclear texture (heterogeneity, granularity, condensation, radial distribution) related to the cell cycle progression of cells that are maintained alive.     

Repeatability of Quantitative MRI Measurements in Normal Breast Tissue

PURPOSE: To evaluate the variability and repeatability of repeated magnetic resonance imaging (MRI) measurements in normal breast tissues between and within subjects. METHODS: Eighteen normal premenopausal subjects underwent two contrast-enhanced MRI scans within 72 hours or during the same menstrual phase in two consecutive months. A subset of nine women also completed diffusion-weighted imaging (DWI). Fibroglandular tissue (FGT) density and FGT enhancement were measured on the contrast-enhanced MRI. Apparent diffusion coefficient (ADC) values were computed from DWI. Between- and within-subject coefficients of variation (bCV and wCV, respectively) were assessed. Repeatability of all measurements was assessed by the coefficient of repeatability (CR) and Bland-Altman plots. RESULTS: The bCV of FGT density and FGT enhancement at visit 1 and visit 2 ranged from 47% to 63%. The wCV was 13% for FGT density, 22% for FGT enhancement, and 11% for ADC. The CRs of FGT density and FGT enhancement were 0.15 and 0.19, respectively, and for ADC, it was 6.1 x 10^-4 mm²/s. CONCLUSIONS: We present an estimate of the variability and repeatability of MR measurements in normal breasts. These estimates provide the basis for understanding the normal variation of healthy breast tissue in MRI and establishing thresholds for agreement between measurements.     

The Correlation of Contrast-Enhanced Ultrasound and MRI Perfusion Quantitative Analysis in Rabbit VX2 Liver Cancer

Our objective is to explore the value of liver cancer contrast-enhanced ultrasound (CEUS) and MRI perfusion quantitative analysis in liver cancer and the correlation between these two analysis methods. Rabbit VX2 liver cancer model was established in this study. CEUS was applied. Sono Vue was applied in rabbits by ear vein to dynamically observe and record the blood perfusion and changes in the process of VX2 liver cancer and surrounding tissue. MRI perfusion quantitative analysis was used to analyze the mean enhancement time and change law of maximal slope increasing, which were further compared with the pathological examination results. Quantitative indicators of liver cancer CEUS and MRI perfusion quantitative analysis were compared, and the correlation between them was analyzed by correlation analysis. Rabbit VX2 liver cancer model was successfully established. CEUS showed that time–intensity curve of rabbit VX2 liver cancer showed “fast in, fast out” model while MRI perfusion quantitative analysis showed that quantitative parameter MTE of tumor tissue increased and MSI decreased: the difference was statistically significant (P < 0.01). The diagnostic results of CEUS and MRI perfusion quantitative analysis were not significantly different (P > 0.05). However, the quantitative parameter of them were significantly positively correlated (P < 0.05). CEUS and MRI perfusion quantitative analysis can both dynamically monitor the liver cancer lesion and surrounding liver parenchyma, and the quantitative parameters of them are correlated. The combined application of both is of importance in early diagnosis of liver cancer.     

梨果实肉质遗传模式的探讨

根据3种类型梨杂交组合后代的遗传表现,提出梨果实肉质遗传模式为:梨果实肉质的脆软肉遗传为质量性状遗传,由A、B两对基因控制。软肉对脆肉为显性,只有两对基因同时隐性纯合时才表现为脆肉。脆肉基因型为aa bb,软肉基因型为A_ _ _、_ _B_,该模式可解释前人的部分研究成果。 Abstract:The crispness and softness of flesh texture in pear are qualitative characters,controlled by two genes A,B.The softness is dominant to crispness,only when two genes are recessive homozygous,the phenotype is crispness.The genotype of crispness is aabb,the genotypes of softness are A_ _ _,_ _ B_,Some factors may affect flesh also.     

Abnormal Regional Homogeneity in Patients with Essential Tremor Revealed by Resting-State Functional MRI

Essential tremor (ET) is one of the most common movement disorders in human adults. It can be characterized as a progressive neurological disorder of which the most recognizable feature is a tremor of the arms or hands that is apparent during voluntary movements such as eating and writing. The pathology of ET remains unclear. Resting-state fMRI (RS-fMRI), as a non-invasive imaging technique, was employed to investigate abnormalities of functional connectivity in ET in the brain. Regional homogeneity (ReHo) was used as a metric of RS-fMRI to assess the local functional connectivity abnormality in ET with 20 ET patients and 20 age- and gender-matched healthy controls (HC). The ET group showed decreased ReHo in the anterior and posterior bilateral cerebellar lobes, the bilateral thalamus and the insular lobe, and increased ReHo in the bilateral prefrontal and parietal cortices, the left primary motor cortex and left supplementary motor area. The abnormal ReHo value of ET patients in the bilateral anterior cerebellar lobes and the right posterior cerebellar lobe were negatively correlated with the tremor severity score, while positively correlated with that in the left primary motor cortex. These findings suggest that the abnormality in cerebello-thalamo-cortical motor pathway is involved in tremor generation and propagation, which may be related to motor-related symptoms in ET patients. Meanwhile, the abnormality in the prefrontal and parietal regions may be associated with non-motor symptoms in ET. These findings suggest that the ReHo could be utilized for investigations of functional-pathological mechanism of ET.     

3D Texture Analysis Reveals Imperceptible MRI Textural Alterations in the Thalamus and Putamen in Progressive Myoclonic Epilepsy Type 1, EPM1

Progressive myoclonic epilepsy type 1 (EPM1) is an autosomal recessively inherited neurodegenerative disorder characterized by young onset age, myoclonus and tonic-clonic epileptic seizures. At the time of diagnosis, the visual assessment of the brain MRI is usually normal, with no major changes found later. Therefore, we utilized texture analysis (TA) to characterize and classify the underlying properties of the affected brain tissue by means of 3D texture features. Sixteen genetically verified patients with EPM1 and 16 healthy controls were included in the study. TA was performed upon 3D volumes of interest that were placed bilaterally in the thalamus, amygdala, hippocampus, caudate nucleus and putamen. Compared to the healthy controls, EPM1 patients had significant textural differences especially in the thalamus and right putamen. The most significantly differing texture features included parameters that measure the complexity and heterogeneity of the tissue, such as the co-occurrence matrix-based entropy and angular second moment, and also the run-length matrix-based parameters of gray-level non-uniformity, short run emphasis and long run emphasis. This study demonstrates the usability of 3D TA for extracting additional information from MR images. Textural alterations which suggest complex, coarse and heterogeneous appearance were found bilaterally in the thalamus, supporting the previous literature on thalamic pathology in EPM1. The observed putamenal involvement is a novel finding. Our results encourage further studies on the clinical applications, feasibility, reproducibility and reliability of 3D TA.     

Automatic ROI Selection in Structural Brain MRI Using SOM 3D Projection

This paper presents a method for selecting Regions of Interest (ROI) in brain Magnetic Resonance Imaging (MRI) for diagnostic purposes, using statistical learning and vector quantization techniques. The proposed method models the distribution of GM and WM tissues grouping the voxels belonging to each tissue in ROIs associated to a specific neurological disorder. Tissue distribution of normal and abnormal images is modelled by a Self-Organizing map (SOM), generating a set of representative prototypes, and the receptive field (RF) of each SOM prototype defines a ROI. Moreover, the proposed method computes the relative importance of each ROI by means of its discriminative power. The devised method has been assessed using 818 images from the Alzheimer''s disease Neuroimaging Initiative (ADNI) which were previously segmented through Statistical Parametric Mapping (SPM). The proposed algorithm was used over these images to parcel ROIs associated to the Alzheimer''s Disease (AD). Additionally, this method can be used to extract a reduced set of discriminative features for classification, since it compresses discriminative information contained in the brain. Voxels marked by ROIs which were computed using the proposed method, yield classification results up to 90% of accuracy for controls (CN) and Alzheimer''s disease (AD) patients, and 84% of accuracy for Mild Cognitive Impairment (MCI) and AD patients.     

Brain Development after Neonatal Intermittent Hyperoxia-Hypoxia in the Rat Studied by Longitudinal MRI and Immunohistochemistry

Background

Neonatal intermittent hyperoxia-hypoxia (IHH) is involved in the pathogenesis of retinopathy of prematurity. Whether similar oxygen fluctuations will create pathological changes in the grey and white matter of the brain is unknown.

Methods

From birth until postnatal day 14 (P14), two litters (total n = 22) were reared in IHH: hyperoxia (50% O₂) interrupted by three consecutive two-minute episodes of hypoxia (12% O₂) every sixth hour. Controls (n = 8) were reared in room-air (20.9% O₂). Longitudinal MRI (Diffusion Tensor Imaging and T₂-mapping) was performed on P14 and P28 and retinal and brain tissue were examined for histopathological changes. Long-term neurodevelopment was assessed on P20 and P27.

Results

Mean, radial and axial diffusivity were higher in white matter of IHH versus controls at P14 (p < 0.04), while fractional anisotropy (FA) was lower in the hippocampal fimbria and tended to be lower in corpus callosum (p = 0.08) and external capsule (p = 0.05). White matter diffusivity in IHH was similar to controls at P28. Higher cortical vessel density (p = 0.005) was observed at P14. Cortical and thalamic T₂-relaxation time and mean diffusivity were higher in the IHH group at P14 (p ≤ 0.03), and albumin leakage was present at P28. Rats in the IHH group ran for a longer time on a Rotarod than the control group (p ≤ 0.005). Pups with lower bodyweight had more severe MRI alterations and albumin leakage.

Conclusion

IHH led to subtle reversible changes in brain white matter diffusivity, grey matter water content and vascular density. However, alterations in blood-brain barrier permeability may point to long-term effects. The changes seen after IHH exposure were more severe in animals with lower bodyweight and future studies should aim at exploring possible interactions between IHH and growth restriction.     

Cerebral Correlates of Abnormal Emotion Conflict Processing in Euthymic Bipolar Patients: A Functional MRI Study

Background

Patients with bipolar disorder experience cognitive and emotional impairment that may persist even during the euthymic state of the disease. These persistent symptoms in bipolar patients (BP) may be characterized by disturbances of emotion regulation and related fronto-limbic brain circuitry. The present study aims to investigate the modulation of fronto-limbic activity and connectivity in BP by the processing of emotional conflict.

Methods

Fourteen euthymic BP and 13 matched healthy subjects (HS) underwent functional magnetic resonance imaging (fMRI) while performing a word-face emotional Stroop task designed to dissociate the monitoring/generation of emotional conflict from its resolution. Functional connectivity was determined by means of psychophysiological interaction (PPI) approach.

Results

Relative to HS, BP were slower to process incongruent stimuli, reflecting higher amount of behavioral interference during emotional Stroop. Furthermore, BP showed decreased activation of the right dorsolateral prefrontal cortex (DLPFC) during the monitoring and a lack of bilateral amygdala deactivation during the resolution of the emotional conflict. In addition, during conflict monitoring, BP showed abnormal positive connectivity between the right DLPFC and several regions of the default mode network.

Conclusions

Overall, our results highlighted dysfunctional processing of the emotion conflict in euthymic BP that may be subtended by abnormal activity and connectivity of the DLPFC during the conflict monitoring, which, in turn, leads to failure of amygdala deactivation during the resolution of the conflict. Emotional dysregulation in BP may be underpinned by a lack of top-down cognitive control and a difficulty to focus on the task due to persistent self-oriented attention.