Automatic Identification of Miscarriage Cases Supported by Decision Strength Using Ultrasound Images of the Gestational Sac

Ultrasound imaging is one of the most widely used multipurpose imaging modalities for monitoring and diagnosing early pregnancy events. The first sign and measurable element of an early pregnancy is the appearance of the Gestational Sac (GS). Currently, the size of the GS is manually estimated from ultrasound images. The manual measurements tend to result in inter- and intraobserver variations, which may lead to difficulties in diagnosis. This paper proposes a new method for automatic identification of miscarriage cases in the first trimester of pregnancy. The proposed method automatically segments the GS and calculates the Mean Sac Diameter (MSD) and other geometric features of the segmented sac. After classifying the image based on the extracted features into either a pregnancy of unknown viability (PUV) or a possible miscarriage case, we assign the decision with a strength level to reflect its reliability. The paper argues that the level of decision strength gives more insight into decision making than other classical alternatives and makes the automated decision process closer to the diagnosis practice by exper

Computer-aided diagnosis of gynaecological abnormality using B-mode ultrasound images

Ultrasound scan is one of the most reliable imaging for detecting/diagnosing of gynaecological abnormalities. Ultrasound imaging is widely used during pregnancy and has become central in the management of the problems of early pregnancy, particularly in miscarriage diagnosis. Also ultrasound is considered as the most important imaging modality in the evaluation of different types of ovarian tumours. The early detection of ovarian carcinoma and miscarriage continues to be a challenging task. It mostly relies on manual examination, interpretation by gynaecologists, of the ultrasound scan images that may use morphology features extracted from the region of interest. Diagnosis depends on using certain scoring systems that have been devised over a long time. The manual diagnostic process involves multiple subjective decisions, with increased inter- and intra-observer variations which may lead to serious errors and health implications. This thesis is devoted to developing computer-based tools that use ultrasound scan images for automatic classification of Ovarian Tumours (Benign or Malignant) and automatic detection of Miscarriage cases at early stages of pregnancy. Our intended computational tools are meant to help gynaecologists to improve accuracy of their diagnostic decisions, while serving as a tool for training radiology students/trainees on diagnosing gynaecological abnormalities. Ultimately, it is hoped that the developed techniques can be integrated into a specialised gynaecology Decision Support System. Our approach is to deal with this problem by adopting a standard image-based pattern recognition research framework that involve the extraction of appropriate feature vector modelling of the investigated tumours, select appropriate classifiers, and test the performance of such schemes using sufficiently large and relevant datasets of ultrasound scan images. We aim to complement the automation of certain parameters that gynaecologist experts and radiologists manually determine, by image-content information attributes that may not be directly accessible without advanced image transformations. This is motivated by, and benefit from, advances in computer vision that led the emergence of a variety of image processing/analysis techniques together with recent advances in data mining and machine learning technologies. An expert observer makes a diagnostic decision with a level of certainty, and if not entirely certain about their diagnostic decisions then often other experts’ opinions are sought and may be essential for diagnosing difficult “Inconclusive cases”. Here we define a quantitative measure of confidence in decisions made by automatic diagnostic schemes, independent of accuracy of decision. In the rest of the thesis, we report on the development of a variety of innovative diagnostic schemes and demonstrate their performances using extensive experimental work. The following is a summary of the main contributions made in this thesis. 1. Using a combination of spatial domain filters and operations as pre-processing procedures to enhance ultrasound images for both applications, namely miscarriage identification and ovarian tumour diagnosis. We show that the Non-local means filter is effective in reducing speckle noise from ultrasound images, and together with other filters we succeed in enhancing the inner border of malignant tumours and reliably segmenting the gestational sac. 2. Developing reliable automated procedures to extract several types of features to model gestational sac dimensional measurements, few of which are manually determined by radiologist and used by gynaecologists to identify miscarriage cases. We demonstrate that the corresponding automatic diagnostic schemes yield excellent accuracy when classified by the k-Nearest Neighbours. 3. Developing several local as well as global image-texture based features in the spatial as well as the frequency domains. The spatial domain features include the local versions of image histograms, first order statistical features and versions of local binary patterns. From the frequency domain, we propose a novel set of Fast Fourier Geometrical Features that encapsulates the image texture information that depends on all image pixel values. We demonstrate that each of these features define Ovarian Tumour diagnostic scheme that have relatively high power of discriminating Benign from Malignant tumours when classified by Support Vector Machine. We show that the Fast Fourier Geometrical Features are the best performing scheme achieving more than 85% accuracy. 4. Introducing a simple measure of confidence to quantify the goodness of the automatic diagnostic decision, regardless of decision accuracy, to emulate real life medical diagnostics. Experimental work in this theis demonstrate a strong link between this measure and accuracy rate, so that low level of confidence could raise an alarm. 5. Conducting sufficiently intensive investigations of fusion models of multi-feature schemes at different level. We show that feature level fusion yields degraded performance compared to all its single components, while score level fusion results in improved results and decision level fusion of three sets of features using majority rule is slightly less successful. Using the measure of confidence is useful in resolving conflicts when two sets of features are fused at the decision level. This leads to the emergence of a Not Sure decision which is common in medical practice. Considering the Not Sure label is a good practice and an incentive to conduct more tests, rather than misclassification, which leads to significantly improved accuracy. The thesis concludes with an intensive discussion on future work that would go beyond improving performance of the developed scheme to deal with the corresponding multi-class diagnostics essential for a comprehensive gynaecology Decision Support System tool as the ultimate goal

Use of high-frequency ultrasound to study the prenatal development of cranial neural tube defects and hydrocephalus in Gldc-deficient mice

Objective: We used non-invasive high-frequency ultrasound (HFUS) imaging to investigate embryonic brain development in a mouse model for neural tube defects (NTDs) and non-ketotic hyperglycinemia (NKH). Method: Using HFUS, we imaged embryos carrying loss of function alleles of Gldc encoding glycine decarboxylase, a component of the glycine cleavage system in mitochondrial folate metabolism, which is known to be associated with cranial NTDs and NKH in humans. We serially examined the same litter during the second half of embryonic development and quantified cerebral structures. Genotype was confirmed using PCR. Histology was used to confirm ultrasound findings. Results: High-frequency ultrasound allowed in utero detection of two major brain abnormalities in Gldc-deficient mouse embryos, cranial NTDs (exencephaly) and ventriculomegaly (corresponding with the previous finding of post-natal hydrocephalus). Serial ultrasound allowed individual embryos to be analysed at successive gestational time points. From embryonic day 16.5 to 18.5, the lateral ventricle volume reduced in wild-type and heterozygous embryos but increased in homozygous Gldc-deficient embryos. Conclusion: Exencephaly and ventriculomegaly were detectable by HFUS in homozygous Gldc-deficient mouse embryos indicating this to be an effective tool to study CNS development. Longitudinal analysis of the same embryo allowed the prenatal onset and progression of ventricle enlargement in Gldc-deficient mice to be determined

Biomechanical Simulations of Human Pregnancy: Patient-Specific Finite Element Modeling

Preterm birth (PTB) is the leading cause of childhood death and effects 10% of babies worldwide. First-time diagnosis is difficult, and as many as 95% of all PTBs are intractable to current therapies. The processes of both preterm labor and normal parturition are poorly understood, in part because pregnancy is a protected environment where experimentation contains the risk of causing harm to the gestation and fetus. This proposes the need for non-invasive investigations to understand both normal and high-risk pregnancies. Furthermore, each pregnancy can vary significantly which adds the complex need for patient-specific investigations. To address this need, we propose the development of parameterized ultrasound-based finite element analyses to study the mechanics of the womb. As a first step, this dissertation work conducts sensitivity analyses on cervical, uterine, and fetal membrane parameters as well as model boundary conditions to determine which factors have the greatest impact on cervical tissue stretch. The effects of the range of patient geometries and material properties are reported. Findings show that a soft and short cervix result in greatest stretch at the internal os, and fetal membrane detachment increases cervical stretch. Additionally, patient-specific finite element analyses are performed on low- and high-risk cohorts and results between the two are compared. Patient geometries are documented at various gestational timepoints, and the effect of a cervical pessary is determined based on changes in cervical geometry and stiffness. Findings showed that a soft cervix correlates with sooner delivery, and that high pessary placement is ideal to decrease stretch at the internal os

Novel biochemical markers in the diagnosis and management of early pregnancy problem

Background and purpose: Early pregnancy problems, including miscarriage, ectopic pregnancy and pregnancy of unknown location, occur commonly and have significant medical, psychological and economic consequences. Biochemical markers are increasingly being used as an adjunct to ultrasonography and this thesis describes three studies exploring the use of novel biochemical markers in the diagnosis and management of early pregnancy problems. Materials and methods: These are observational studies of women in early pregnancy recruited at Sunderland Royal Hospital and King’s College Hospital. Serum samples were taken from women in early pregnancy and lectin affinity chromatography used to characterise the glycosylation of hCG by gestational age and by pregnancy outcome. Women with a diagnosis of a miscarriage, ectopic pregnancy or pregnancy of unknown location had serum levels of hCG, progesterone, inhibin A, IGFBP-1 and inhibin proαC quantified, and statistical analysis was used to see if spontaneous resolution of the pregnancies could be predicted. Results: Lectin-affinity chromatography reveals five major glyco-isoforms of hCG in early pregnancy, the expression of which changes with gestational age and by pregnancy outcome. The novel markers of the luteo-trophoblastic axis inhibin A, IGFBP-1 and inhibin proαC are found not to be clinically useful in the prediction of spontaneously resolving PULs although when used in the decision trees developed by Elson in 2005, they are useful for predicting spontaneous resolution of miscarriages and failed pregnancies. Conclusions: Novel biochemical markers have the potential to be a useful addition in the management of early pregnancy problems. Further studies are required to explore the physiological basis of these findings and the clinical applicability of these tools.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

An Affordable Portable Obstetric Ultrasound Simulator for Synchronous and Asynchronous Scan Training

The increasing use of Point of Care (POC) ultrasound presents a challenge in providing efficient training to new POC ultrasound users. In response to this need, we have developed an affordable, compact, laptop-based obstetric ultrasound training simulator. It offers freehand ultrasound scan on an abdomen-sized scan surface with a 5 degrees of freedom sham transducer and utilizes 3D ultrasound image volumes as training material. On the simulator user interface is rendered a virtual torso, whose body surface models the abdomen of a particular pregnant scan subject. A virtual transducer scans the virtual torso, by following the sham transducer movements on the scan surface. The obstetric ultrasound training is self-paced and guided by the simulator using a set of tasks, which are focused on three broad areas, referred to as modules: 1) medical ultrasound basics, 2) orientation to obstetric space, and 3) fetal biometry. A learner completes the scan training through the following three steps: (i) watching demonstration videos, (ii) practicing scan skills by sequentially completing the tasks in Modules 2 and 3, with scan evaluation feedback and help functions available, and (iii) a final scan exercise on new image volumes for assessing the acquired competency. After each training task has been completed, the simulator evaluates whether the task has been carried out correctly or not, by comparing anatomical landmarks identified and/or measured by the learner to reference landmark bounds created by algorithms, or pre-inserted by experienced sonographers. Based on the simulator, an ultrasound E-training system has been developed for the medical practitioners for whom ultrasound training is not accessible at local level. The system, composed of a dedicated server and multiple networked simulators, provides synchronous and asynchronous training modes, and is able to operate with a very low bit rate. The synchronous (or group-learning) mode allows all training participants to observe the same 2D image in real-time, such as a demonstration by an instructor or scan ability of a chosen learner. The synchronization of 2D images on the different simulators is achieved by directly transmitting the position and orientation of the sham transducer, rather than the ultrasound image, and results in a system performance independent of network bandwidth. The asynchronous (or self-learning) mode is described in the previous paragraph. However, the E-training system allows all training participants to stay networked to communicate with each other via text channel. To verify the simulator performance and training efficacy, we conducted several performance experiments and clinical evaluations. The performance experiment results indicated that the simulator was able to generate greater than 30 2D ultrasound images per second with acceptable image quality on medium-priced computers. In our initial experiment investigating the simulator training capability and feasibility, three experienced sonographers individually scanned two image volumes on the simulator. They agreed that the simulated images and the scan experience were adequately realistic for ultrasound training; the training procedure followed standard obstetric ultrasound protocol. They further noted that the simulator had the potential for becoming a good supplemental training tool for medical students and resident doctors. A clinic study investigating the simulator training efficacy was integrated into the clerkship program of the Department of Obstetrics and Gynecology, University of Massachusetts Memorial Medical Center. A total of 24 3rd year medical students were recruited and each of them was directed to scan six image volumes on the simulator in two 2.5-hour sessions. The study results showed that the successful scan times for the training tasks significantly decreased as the training progressed. A post-training survey answered by the students found that they considered the simulator-based training useful and suitable for medical students and resident doctors. The experiment to validate the performance of the E-training system showed that the average transmission bit rate was approximately 3-4 kB/s; the data loss was less than 1% and no loss of 2D images was visually detected. The results also showed that the 2D images on all networked simulators could be considered to be synchronous even though inter-continental communication existed

Ultrasound Imaging

This book provides an overview of ultrafast ultrasound imaging, 3D high-quality ultrasonic imaging, correction of phase aberrations in medical ultrasound images, etc. Several interesting medical and clinical applications areas are also discussed in the book, like the use of three dimensional ultrasound imaging in evaluation of Asherman's syndrome, the role of 3D ultrasound in assessment of endometrial receptivity and follicular vascularity to predict the quality oocyte, ultrasound imaging in vascular diseases and the fetal palate, clinical application of ultrasound molecular imaging, Doppler abdominal ultrasound in small animals and so on