Current Medical Imaging - Volume 13, Issue 2, 2017

Population of aged people is on the rise worldwide, thanks to the advances in medicine, which enhanced lifespan. However, this increased lifespan came with a price, that is, aging associated diseases, of which diseases affecting central nervous system, in particular, stroke, Alzheimer's disease, Huntington's disease etc., are predominant. Inasmuch as intervention and access to brain is not always possible by invasive techniques, it is essential to develop non-invasive methods that can give a clue at molecular level regarding the pathological mechanisms in brain regions. Recent advances in neuroradiological and imaging techniques have helped in early and differential diagnosis of several neurological diseases and the underlying molecular mechanisms. Among these, Positron Emission Tomography (PET) holds great promise in the early diagnosis of Alzhemier's disease, etc. The present review article focuses on the current views, latest developments and reported shortcomings of the versatile imaging technique PET. An important aspect of PET is the specificity of neuroimaging agents, as these often have undesirably high non-specific binding to brain tissue and we address this and discuss the recent advances in the development of these agents as well as the specific biomarkers for neuroimaging.

Recent advances in the treatment of cerebral gliomas have increased the demand for diagnosis by means of neuroimaging in order to assist in treatment planning and prognosis. Advanced magnetic resonance (MR) imaging techniques, including MR spectroscopy (MRS) and MR perfusion, have proved invaluable in evaluating key pathological features of gliomas. MRS provides a broad range of information about cell membrane proliferation, neuronal integrity, energy metabolism, and necrosis of tumor tissue, while perfusion MR imaging provides valuable information about tumor neoangiogenesis. Together these imaging techniques aid in the grading of a glioma, a necessary step before planning a course of treatment. This report provides an up-to-date review of brain MRS and MR perfusion techniques and discusses their potential roles in glioma grading.

Breast cancer is a familiar disease in the female; its effects are, however, not so much diverse in males. In females, the death rate is gradually increasing due to this disease because rarely its sign and symptoms appear at an initial phase that makes it hard to detect at an early stage. As breast cancer has developed into the rapidly growing disease among women, numerous detection methods, algorithms and new technologies and machinery are introduced in the market for its early detection. Computer aided diagnosis and detection system proved to be an efficient tool for early detection of breast tumor. Various techniques have been presented by researchers for the improved performance of CAD systems for diagnosis/detection of breast masses. The aim of this rese arch work is to present a concise review of different imaging modalities and techniques with their performance assessment in different stages of an automated or computer aided detection system (CAD) for breast tumor detection. The most commonly used imaging modalities are discussed like mammography, MRI, and ultrasound for breast cancer detection and diagnostic purposes. A detailed discussion of different imaging modalities, datasets, performance measures and various techniques used for the automated detection of a breast tumor with recent advances and evaluation of their performance in different steps of computer-aided diagnosis and detection systems is presented here.

Hepatocellular carcinoma (HCC) is the most common primary liver cancer, which develops mostly in the setting of chronic liver disease. European Association for the Study of the Liver (EASL) and European Organization for Research and Treatment of Cancer (EORTC) prepared guidelines for screening, follow-up and diagnosis of HCC to facilitate decision making and optimize both diagnostic and therapeutic protocols. The review briefly describes etiology, epidemiology and histopathology of HCC and presents EASL-EORTC guidelines for surveillance and diagnosis of HCC. Target population and screening algorithm is presented in the surveillance section. Ultrasound imaging of HCC and the role of contrast enhanced ultrasound are described as well as the value of laboratory tests in screening. Further, radiological features of HCC in multiphase CT and dynamic contrast enhanced MRI and diagnostic criteria are presented. Additionally, the advantages of advanced techniques in MRI such as diffusion weighed imaging and the use of hepatocyte-specific contrast agents are discussed. Lastly, the EASL-EORTC guidelines are compared with the guidelines of the American Association for the Study of Liver Diseases and the Japan Society of Hepatology. Also LI-RADS and the Barcelona Clinic Liver Cancer classification are mentioned. In the near future, due to the ongoing advances in imaging a revision of the guidelines may be expected.

Coronary CT angiography has been increasingly used to diagnose coronary artery disease with high diagnostic value achieved. For further assessment of coronary lumen stenosis, coronary CT angiography allows characterization of coronary plaques in terms of plaque morphology and composition. Coronary plaques are commonly assessed on 2D axial and multiplanar reformatted images. However, these visualization tools are limited to viewing extraluminal changes in the coronary artery but fail to provide intraluminal appearances of the coronary wall due to presence of plaques. In this pictorial essay, we present various intraluminal appearances of coronary wall and plaques with use of 3D virtual intravascular endoscopy (VIE) visualization in relation to different types of plaques. VIE appearances of coronary stents in patients treated with coronary stenting are also briefly demonstrated to show both normal stents and in-stent restenosis.

Ultrasound is a form of mechanical waves that can traverse non-invasively through the human body up to some extent. Because of this non-invasive ability to penetrate through tissues and reflect back, ultrasound has found many applications in medicine for imaging inner organs to understand pathology and help diagnosing disease and also for therapeutic applications such as low back pain treatment, as ultrasound waves transmit energy and can generate local heat production in a focused area. In this article, we have reviewed the current state of knowledge on the therapeutic applications of ultrasound in the injuries of cartilage, knee joint, fresh bone fractures, and also cancers. While low intensity ultrasound has been found to act as an anabolic stimulator for cartilage regeneration, high intensity focused ultrasound has applications in precise tissue ablation of different types of tumors. Further, role of ultrasound in micro bubble mediated ultrasound therapy has been discussed for the efficient delivery of intravascularly administered drugs or genes to targeted tissues during cancer.

Non-squamous cell neoplasms (non-SCCs) are rare tumors of the oropharynx and oral cavity. They can be of many different histologic types, either benign or malignant, including in decreasing order of frequency minor salivary gland tumors, lymphoma, mesenchymal tumors, melanoma, and metastases. Unlike squamous cell carcinoma, non-SCCs could remain unidentified on clinical examination/endoscopy, because they usually manifest as submucosal masses without mucosal alterations. Diagnostic imaging, as CT and, more accurately, MR, plays an essential role in the work- up of these neoplasms, mainly in the staging and follow-up. Furthermore, radiologic features can, to a certain extent, help evaluate a lesion as more likely benign or malignant. More significantly, although generally non-specific, they can suggest or even allow the correct diagnosis in some cases, as pleomorphic adenoma, lymphoma, lipoma, hemangioma, neurofibroma, liposarcoma, and melanoma, especially if integrated with clinical/endoscopic findings and histologic knowledge. In this article, we illustrate CT and MR features of oropharyngeal and oral cavity non-SCCs taken from our experience, with clinical-histologic correlation, and review the literature on the topic.

Traditional pencil sketches drawn by skilled pencil sketch artists are a product of illustration based on exaggeration; there is always some amount of discrepancy between the description of eye-witnesses and depiction of the offender by the sketch artist. To overcome this difficulty, law enforcement agencies worldwide have started using composite sketches (sketches created using computer). Composite sketches have obviated the need of a skilled sketch artist. Composite sketches can be easily drawn by eyewitnesses using face design system software (SketchCop FACETTE) in a very short time period without any prior specialized software training. Matching composite sketches with photos available in database are still a challenging task. In this paper, a novel technique is proposed to match composite sketches with photos available in database. The key contribution of the proposed system in this paper is an efficient and novel methodology developed to match composite sketches with photos available in databases which could be used by law enforcement agencies. The photos taken from law enforcement agencies databases are passed to face detection module. On the detected faces and composite sketches, feature extraction and classification are performed using Multi-resolution uniform Local Binary Pattern (LBP) and Probabilistic Neural Network (PNN) to generate score 1. Similarly, on detected faces and composite sketches, feature extraction and classification are again performed using Dictionary Matching (DM) to generate score 2. The generated scores are collected using Dempster-Shafer (DS) theory and Proportional Conflict Redistribution rule no. 5 (PCR5). In this study, the authors have performed pilot testing of their technique and results of their analysis are presented to the readers.

The Purpose: The objective of this study is to explore neural correlates of Default Mode Network (DMN) regions in children with attention deficit and hyperactivity disorder (ADHD) using resting-state functional magnetic resonance imaging (rs-fMRI). Methods: The study included ten children with ADHD (aged between 9 and 16) and ten agematched controls. Four DMN regions (medial prefrontal cortex (MPFC), the posterior cingulate cortex (PCC), left and right inferior parietal lobes (IPL) and the corresponding Broadmann areas in each one were used as seeds and their functional connectivity with the whole brain was explored and compared between ADHD and control groups using t-test (p<0.05). Results: We observed that when DMN regions were selected as seeds, the connected regions were different between two groups and were mostly in the right hemisphere in ADHD patients contrary to the left hemisphere in the control group. Conclusion: In conclusion, neural correlates of DMN regions differ in ADHD patients compared to healthy controls. Our findings suggest that in ADHD patients, DMN regions show more connectivity with the right hemisphere of the brain whereas the left hemisphere is more functionally connected with DMN in health controls. Further research is required to explore this atypical DMN connectivity in ADHD using larger cohort.

Live video laparoscopic surgery and visual surveillance has been an important research in the past few years. Laparoscopic surgery is a modern video tracking surgical technique in which operations are performed distantly from their location through small incisions (usually 0.5-1.5 cm) in a different place in the body. The visual surveillance system starts with motion detection or tracking. This motion object detection method, attempts to locate connected regions that define, relate the moving objects within the scene; like frame-to-frame difference, background subtraction and motion analysis, the object is detected and tracked from an enhanced video. For these we have defined two different approaches. First one is the Laparoscope Surgery video and Surveillance video Enhancement (LSSVE) algorithm and another algorithm used for only surveillance application background subtraction algorithm. The main goal of the video enhancement algorithm is many objects or activities of interest occur in a blood vessel and dark environment which cannot be seen easily without enhancement. For this development, we follow three different methods, In the second algorithm of background subtraction using dynamic threshold and a mixture of Gaussian three different methods are used effectively for object detection and compared their basis of performance on the accessible tacking the accurate location and detection. In laparoscope surgery, a camera and light provide feedback to the surgeon, who sees the enlarged and video enhanced surgical elements on a TV monitor. The video surveillance system does frame differences, after the object foreground detection, the parameters like speed, velocity and motion are determined.

Background: De-noising is the main effect produced by image compression at low compression ratios, which alters only the noise parts of images. The difference between the original and manipulated images will be less than the statistical variation when pixel values are sampled from these two images. This study develops a method that determines the quality indication in images using compression. Methods: We use the Kolmogorov-Smirnov (KS) two-sample test to determine if the pixel distribution in compressed images is statistically different from the original and then compare previous reports to find the conceived image compression level. Medical images are first compressed using JPEG2000 at various degrees. The KS test was then used to find whether the two datasets differ significantly. Four different window sizes with ten to one hundred thousand test positions are sampled independently from both the compressed and original images to determine their respective empirical distribution functions. Results: The rates for D over the critical value increased obviously with the increasing of image compression ratio. The rates of D values exceeding the critical values are independent of the numbers of test positions. The conceivable image compression ratio level in this work may be set at 10% below the rejection rate compared with previous reports. Conclusion: The results of this report prove that the KS test can be used to indicate the variation in image quality and results were proven equivalent to PSNR. The potential applications for this method include determining the optimal compression ratio for tele-radiology or image archiving.

Objective: To develop a new content-based image retrieval (CBIR) based computer-aided diagnosis (CAD) scheme to discriminate the lung nodules benign or malignant and to perform a preliminary evaluation of this CAD scheme and its robustness. Methods: Two lung nodule datasets from LIDC-IDRI lung CT database were assembled. Two nodule density related features were computed to represent each nodule. For each queried nodule, a twostep CBIR scheme was applied to retrieve the top ten most similar reference nodules. A classification likelihood value was calculated to predict the malignancy of the lung nodule. To assess the robustness of the CBIR scheme, we first tested this CAD scheme on the second dataset, and then used the second dataset to retrieve the first dataset. To verify the feasibility of the CBIR scheme, classification performance of our scheme was comparied with that of classical classifiers. Results: Through applying a leave-one-out validation method on the first dataset, an area under the ROC curve (AUC) of 0.915 was obtained, and the total classification accuracy was 83.0%. For robustness on the second dataset, the AUC was 0.727, and the total classification accuracy was 66.1%. When we used the second dataset to retrieve the first dataset, the AUC value and the total classification accuracy were 0.751 and 71.3%, respectively. The classification performance of the proposed scheme outperforms that of the classical classifiers. Conclusion: This study demonstrated that (1) a simple and efficient CBIR based CAD scheme applying two nodule density related features achieved high performance for classification of lung nodules and (2) this CAD scheme using CBIR approach also had high robustness performance in the future clinical application.

Background: Visceral bleeding caused by ruptured mycotic aneurysms, especially intracerebral hematoma, is a most serious complication. In such cases, not only surgical techniques but also a variety of modalities such as catheter-based technique is required to comprehensively treat a patient with hemorrhage-induced coagulopathy. Case Reports: We treated an infectious endocarditis (IE) patient with coagulopathy caused by ruptured multiple mycotic aneurysms who underwent endovascular embolization using n-butyl cyanoacrylate (NBCA) and successful surgical removal assisted with catheter-based hemostasis. We also reviewed published literatures about mycotic aneurysm treated using NBCA using PUBMED. Upon review of the existing literature, it was evident that there are only a very limited number of publications related to “infectious” or “mycotic aneurysm” treated using NBCA, and only three case references were retrieved. Conclusion: Catheter-based techniques using n-butyl-2-cyanoacrylate (NBCA) which has been used as a liquid embolic agents is effective for patients with hemorrhage-induced coagulopathy caused by ruptured mycotic aneurysms before surgical treatment.