Texture Analysis and Machine Learning to Predict Pulmonary Ventilation from Thoracic Computed Tomography

Chronic obstructive pulmonary disease (COPD) leads to persistent airflow limitation, causing a large burden to patients and the health care system. Thoracic CT provides an opportunity to observe the structural pathophysiology of COPD, whereas hyperpolarized gas MRI provides images of the consequential ventilation heterogeneity. However, hyperpolarized gas MRI is currently limited to research centres, due to the high cost of gas and polarization equipment. Therefore, I developed a pipeline using texture analysis and machine learning methods to create predicted ventilation maps based on non-contrast enhanced, single-volume thoracic CT. In a COPD cohort, predicted ventilation maps were qualitatively and quantitatively related to ground-truth MRI ventilation, and both maps were related to important patient lung function and quality-of-life measures. This study is the first to demonstrate the feasibility of predicting hyperpolarized MRI-based ventilation from single-volume, breath-hold thoracic CT, which has potential to translate pulmonary ventilation information to widely available thoracic CT imaging

Assessment of histopathological methods of evaluating response to neoadjuvant therapy in oesophageal and gastric adenocarcinoma

Upper gastrointestinal tract (GIT) cancers usually receive neoadjuvant therapy prior to surgery. The histological assessment of this response and if this can be predicted on the pre-treatment biopsy are the subject of this thesis. The first study assessed the inter- and intra-observer variation amongst pathologists in evaluating the degree of regression using the Mandard scoring system. The results showed that the reproducibility of this system was only fair to moderate in both cases of inter- and intra-observer testing. The second study examined the levels of expression of selected tumour markers before and after neoadjuvant chemotherapy. These included markers monitoring apoptosis (p53 and bcl-2), proliferation (Ki-67), angio- and lymphangio-genesis (VEGF, CD-31 and LYVE-1). The levels of expression in these markers were measured in the pre-treatment biopsies, to monitor if they could predict the response to neoadjuvant therapy. It was found that when the panel of chosen markers being used together, delivered a much higher power of prediction rather than adopting only one marker, where the collective power of prediction was 80.6%, whereas individually, the power of prediction ranged between 24.6% (VEGF) and 60.7% (Ki-67). The third study explored the use of digital image analysis in assessing the response to neoadjuvant therapy. It was found that while this technique paralleled the Mandard scoring system, it delivered a more objective and reproducible assessment. On the basis of these results I suggest that image analysis should be used to assess tumour regression especially in the context of clinical trials. In this retrospective study it has been shown that the pre-treatment biopsy can predict the degree of regression

Does airway pathology in severe preschool wheezers predict childhood asthma?

Although one third of all preschool children wheeze, only half of these will have persistent symptoms and go on to have asthma at school age. Pathological changes characteristic of asthma, including eosinophilic inflammation and increased reticular basement membrane thickness, were evident in endobronchial biopsies from severe recurrent wheezers aged 2-3 years when compared with age matched controls. However, at the time of endobronchial biopsy it was not known which children would persistently wheeze and develop asthma at school age. The work of this thesis follows up this group of children, both preschool wheezers (n=47) and non-wheezing controls (n=21), aged between 6-11 years and establishes the presence or absence of school age asthma, relating this to pre-school airway pathology. Children (n=51) were followed up at school age, and those who attended for the research visit (n=39) were characterised in terms of atopic status, lung function (spirometry, lung clearance index) and airway inflammation (exhaled nitric oxide) at school age. Forty percent (15/37) of preschool wheezers had developed asthma at school age. Although increased airway smooth muscle is an established pathological feature of asthma in school age children, nothing is known about airway smooth muscle in preschool wheezers, hence airway smooth muscle, smooth muscle mast cells and reticular basement membrane tenascin-C were measured in the endobronchial biopsies taken at preschool age. Next, airway remodelling (increased airway smooth muscle and increased reticular basement membrane thickness) and airway inflammation at preschool age were related to the presence or absence of asthma at school age. Sixty two percent (42/68) of children had one or more evaluable biopsies for airway smooth muscle assessment. Although reticular basement membrane thickness and submucosal eosinophils were significantly higher in preschool wheezers compared with controls, they did not discriminate the children who developed asthma by school age, suggesting these airway pathological features may be associated with current symptoms rather than future asthma risk. In contrast preschool airway smooth muscle was increased in those severe preschool wheezers who went on to develop school age asthma (n=8, median age 8.2 [6-10.4] years, median ASM 0.12 [0.08-0.16]) when compared with those who did not develop asthma (n=24, median age 7.3 [5.9-11] years, median ASM 0.07 [0.02-0.23]), p=0.007. These data suggest that future studies investigating the mechanisms underlying the persistence of preschool wheeze and its development to asthma should have a primary focus on airway smooth muscle

Stereology and automated measurement of the human brain

Stereology supplies image sampling rules to estimate geometric quantities such as volume, surface area, feature length and number. The method is well suited to non-invasive image acquisition methods such as Magnetic Resonance Imaging (MRI). Meanwhile, in Magnetic Resonance (MR) images analysis area, automated software packages have been continuously developed and become well-established tools especially in human brainMR images processing. The aims of the thesis are (1) to combine proper rules to sample MR images with automated or semi-automated data acquisition methods, in order to implement four different design unbiased stereological volume estimators in the study of the human brain, and (2) to compare volume estimates with those obtained from automated software packages.In volume estimation of three-dimensional (3D) objects, besides one traditional stereological method (i.e. the CAVALIERI method), in recent years a number of newly design-based unbiased methods have been published, which include three used in this thesis (i.e. the ISOTROPIC CAVALIERI (ICAV), INVARIATOR (INV) and DISCRETIZED NUCLEATOR (DN) methods). The ICAV and INV methods both allow the estimation of surface area too. The ICAV method enables volume estimation to be unbiased and precise in individual objects while the INV and DN methods make it efficient to estimate the mean volume of a big cohort. To make it be practical in estimating the volume of human brain solely from MR images, in the thesis the ICAV, INV and DN methods were given two operating protocols for rotation and measurement on a commercial software (i.e. ANALYZE) and were performed in a fetal brain study. The ICAV, INV and DN methods were also programmed in three scripts for rotation, gridding and measurement purposes respectively using three freely available software packages (i.e. FSL, R and IMAGEJ), which were applied in three adult brain studies.In volume estimation of three-dimensional (3D) objects, besides one traditional stereological method (i.e. the CAVALIERI method), in recent years a number of newly design-based unbiased methods have been published, which include three used in this thesis (i.e. the ISOTROPIC CAVALIERI (ICAV), INVARIATOR (INV) and DISCRETIZED NUCLEATOR (DN) methods). The ICAV and INV methods both allow the estimation of surface area too. The ICAV method enables volume estimation to be unbiased and precise in individual objects while the INV and DN methods make it efficient to estimate the mean volume of a big cohort. To make it be practical in estimating the volume of human brain solely from MR images, in the thesis the ICAV, INV and DN methods were given two operating protocols for rotation and measurement on a commercial software (i.e. ANALYZE) and were performed in a fetal brain study. The ICAV, INV and DN methods were also programmed in three scripts for rotation, gridding and measurement purposes respectively using three freely available software packages (i.e. FSL, R and IMAGEJ), which were applied in three adult brain studies.A fetal brain study was carried out to test the application of the ICAV, INV and DN methods. Ten fetuses from three maternal backgrounds (i.e. five healthy, three maternal psychological stress and two maternal substance misuse) were scanned in MRI at both the second and third trimesters of pregnancy. Then fetal brain images were motion corrected using SLIMMER software. Volumes of brain parenchyma (the functional tissue of the brain which is made of two types of brain cells, namely neurons and glia) including ventricles were estimated by the ICAV method in isotropic (i.e. having no preferred orientation) and uniformly random (i.e. uniformly distance (interval) apart) (IUR) triplet of orthogonal section planes (i.e. the ICAV ortrip method) and by the INV and DN methods in isotropically random (IR) triplet of orthogonal section planes through a fixed pivotal point (i.e. the INV ortrip and DN ortrip methods). Due to observation of artefacts in MR images and manual input in the methods, inter- and intra-rater reliability studies were performed to investigate both point counting for the ICAV method and segment length measurement for the INV and DN methods among three raters on five fetal brains from the second and five from the third trimesters. Surface area was also estimated using the ICAV method for error prediction. High reliability (Pearson’s r > 0:997) was shown in inter- and intra-rater studies. In both the second and third trimesters, there were no significant difference in mean volumes of all ten brains estimated by the three methods (p > 0:1). For individual estimates, The predicted coefficients of error (CEs) for the ICAV method were 1:5% ± 0:1% in the second trimester and 2:1% ± 0:1% in the third trimester. Basing on one IR section plane for each data, empirical CEs for the INV method in both trimesters were 19:4% ± 2:9% and 18:5% ± 11:6%, and were 21:4% ± 4:5% and 24:1% ± 11:7% for the DN method. CEs could be decreased to 8.1%, 5.5% for the INV ortrip method and 10.3%, 9.7% for the DN ortrip method in both trimesters. This study showed the ICAV method performed precisely in individual volume measurements while the INV and DN methods worked efficiently in population mean volume estimation. Clinically, no significant differences (p > 0:05) of fetal brain volumes among three maternal groups were detected due to small sample size although potentially in comparison with normal fetal brain, volume might be bigger in the maternal stress group and might be smaller in the substance abused group.As the CAVALIERI method is a design-unbiased method, the main source of potential bias (i.e. if a biased method is applied the mean of the estimated values deviates significantly from the true value) will come from observers in operation who would be the author in this PhD study. To examine whether there is bias caused by the author’s manual point counting procedure in the CAVALIERI method, a slice-by-slice comparison on one adult brain volume estimation on MR images between the CAVALIERI method and an automatically reconstructing software (i.e. FREESURFER) was performed. One healthy elderly (male, age 71) brain MRI scan with good image quality was selected from a dataset of 40 patients affected by the ALZHEIMER’s disease (AD) and 22 healthy elderly volunteers. FREESURFER was used to perform individual volumetric analysis on the adult brain automatically, which outlined grey matter and white matter in the cerebrum on each MR image slice. The CAVALIERI method was applied to a series of coronal images obtained with random starting position and at 1 cm intervals from the TALAIRACH transformed and intensity normalized 3D MR image (i.e. nu.mgz) displayed with the compartment boundaries identified by the FREESURFER pipeline suppressed. The uniformly random (UR) test system for point counting was superimposed on each image. The CAVALIERI method in combination with point counting strategy was used to estimate the volume of cerebrum excluding ventricles (the sum of the two cerebral hemispheres including blood vessels and meninges) using EASYMEASURE software on the grey scale MR images. Additionally, the author overlay the brain boundary segmented by FREESURFER on these selected test points and reassessed the images to compute two scores, namely (i) the total number of test points which had been counted but which were seen to lie outside the FREESURFER segmentation and (ii) total number of the new test points that now needed to be additionally included as lying within the FREESURFER segmentation.. The cerebral volume was 972 cm3 estimated by FREESURFER and 960 cm3 by the author using the CAVALIERI method with CE of 0.34%. FREESURFER had 1.3% bigger measure than that estimated by the author. FREESURFER aided point counting estimate was between 948 cm3 and 982 cm3 with mean volume of 965 cm3. The ratio of points counted by the author but were outside the pial boundary segmented by FREESURFER to total points number counted was between 2.6% to 4.0%, and the ratio of test points not counted by the author but were inside the pial boundary segmented by FREESURFER to total points number counted was between 2.7% to 4.9%. Therefore the author’s estimate was in the range of FREESURFER aided estimation by the CAVALIERI method and both volume ratios were close to each other. No bias could be found between the author using the CAVALIERI method and FREESURFER, which gives the author confidence in performing following studies.Furthermore, volume difference of cerebrum excluding ventricles between AD patients and healthy people were investigated using four stereological methods (i.e. the CAVALIERI, ICAV, INV and DN methods) and the FREESURFER software. From the same dataset of 40 AD patients and 22 healthy elderly volunteers, brain MR images of 13 patients and 13 volunteers were selected with good image quality. Inter-reliability and intra-repeatability studies were performed by two observers on three AD and three normal ageing brains. Both the inter-reliability and intra-repeatability studies showed good consistency. There was no significant difference of individual measures among the CAVALIERI and ICAV methods and FREESURFER. The average time taken for each cerebral volume estimation was less than 15 mins by each of the CAVALIERI, ICAV, INV and DN methods. Clinically, the cerebral volume was significantly smaller in the AD patients, which were found using both the CAVALIERI (p = 0:01) and ICAV (p < 0:01) methods and FREESURFER (p = 0:01) although the INV and DN methods were not able to detect this difference. In this adult brain group study, the volume estimates from the CAVALIERI and ICAV methods were competitive with those obtained from FREESURFER, while the INV and DN methods might be more useful if being applied with a larger sample size or the INV ortrip and DN ortrip methods were applied.Lastly, a systematic investigation on potential imaging biomarkers for AD was performed by the FREESURFER software, one of the imaging biomarkers (i.e. volume ratio of cerebrum excluding ventricles to intra-cranium (the contents of the skull above the level of the foramen magnum)) was re-examined by the INV method manually. From the same dataset of 40 AD patients and 22 healthy elderly volunteers, the brain MR images of 27 AD patients and 16 healthy elderly controls between the maximal common age scope of 47 to 71 were selected, which were analysed by FREESURFER for each brain region. Furthermore, to see the effect of AD on normal ageing atrophy, the difference of volume ratios of each brain region to whole brain between AD patients and healthy controls was investigated. Volume ratios of many brain parenchymal regions (e.g. hippocampus (left p = 0:002, right p < 0:001), amygdala (left p < 0:001, right p < 0:001), accumbens area (left p = 0:002, right p = 0:001), left putamen (p = 0:037) and corpus callosum (mid anterior p = 0:03, mid posterior p = 0:032)) to whole brain were found smaller in AD patients while volume ratios of ventricles (both sides of lateral, inferior lateral and 3rd ventricles, p < 0:001) to whole brain were bigger in AD patients. Besides, the INV method was able to detect significant difference of volume ratio of cerebral parenchyma to intra-cranium between AD patients and healthy elderly subjects too (p < 0:01). In comparison with normal ageing-related atrophy in healthy subjects, brain atrophy with ageing in AD patients presented in a different pattern in volume ratios (e.g. right (p = 0:029) and total cortex (p = 0:013) to brain, total grey matter to brain (p = 0:01), cerebral white matter to brain (p = 0:003), cerebellar cortex to brain (left p = 0:019, right p = 0:032), 5th ventricle to brain (p = 0:048), left fimbria to left hippocampus (p = 0:015), left hippocampal-amygdaloid transition area (HATA) to left hippocampus and right presubiculum to right hippocampus (p = 0:016)). In this AD study, many volume ratios of brain regions to whole brain or other brain regions were found different in AD patients and especially volume ratio of cerebral parenchyma to intra-cranium showed potentiality as an imaging biomarker for AD. Ageing atrophy pattern was found different in AD patients too.In conclusion, by programming in freely available R, FSL and IMAGEJ software packages, the CAVALIERI, ICAV, INV and DN methods were able to be performed conveniently and efficiently on human brain volume estimation using MRI. We made the first applications on the volume estimation of fetal brains, healthy brains and brains affected by AD using the ICAV, INV and DN methods. The volume estimates were competitive with those obtained from automated programme (i.e. FREESURFER)

Experimental Characterization of Vascular Tissue Viscoelasticity with Emphasis on Elastin's Role

Elucidating how cardiovascular biomechanics is regulated during health and disease is critical for developing diagnostic and therapeutic methods. The extracellular matrix of cardiovascular tissue is composed of multiple fibrillar networks embedded in an amorphous ground substance and has been found to reveal time-dependent mechanical behavior. Given the multiscale nature of tissue biomechanics, an accurate description of cardiovascular biomechanics can be obtained only when microstructural morphology is characterized and put together in correlation with tissue-scale mechanics. This study constitutes the initial steps toward a full description of cardiovascular tissue biomechanics by examining two fundamental questions: How does the elastin microstructure change with tissue-level deformations? And how does the extracellular matrix composition affect tissue biomechanics? The outcome of this dissertation is believed to contribute to the field of cardiovascular tissue biomechanics by addressing some of the fundamental existing questions therein. Assessing alterations in microstructural morphology requires quantified measures which can be challenging given the complex, local and interconnected conformations of tissue structural components embedded in the extracellular matrix. In this study, new image-based methods for quantification of tissue microstructure were developed and examined on aortic tissue under different deformation states. Although in their infancy stages of development, the methods yielded encouraging results consistent with existing perceptions of tissue deformation. Changes in microstructure were investigated by examining histological images of deformed and undeformed tissues. The observations shed light on roles of elastin network in regulating tissue deformation. The viscoelastic behavior of specimens was studied using native, collagen-denatured, and elastin-isolated aortic tissues. The stress-relaxation responses of specimens provide insight into the significance of extracellular matrix composition on tissue biomechanics and how the tissue hydration affects the relaxation behavior. The responses were approximated by traditional spring-dashpot models and the results were interpreted in regards to microstructural composition