Current Medical Imaging - Volume 16, Issue 2, 2020

Background: Acute chest pain is one of the most common reasons for Emergency Department (ED) visits and hospital admissions. As this could represent the first symptom of a lifethreatening condition, urgent identification of the etiology of chest pain is of utmost importance in emergency settings. Such high-risk conditions that can present with acute chest pain in the ED include Acute Coronary Syndromes (ACS), Pulmonary Embolisms (PE) and Acute Aortic Syndromes (AAS). Discussion: The concept of Triple Rule-out Computed Tomographic Angiography (TRO-CTA) for patients presenting with acute chest pain in the ED is based on the use of coronary computed tomographic angiography as a single imaging technique, able to diagnose or exclude three lifethreatening conditions in one single step: ACS, AAS and PE. TRO-CTA protocols have been proved to be efficient in the ED for diagnosis or exclusion of life-threatening conditions and for differentiation between various etiologies of chest pain, and application of the TRO-CTA protocol in the ED for acute chest pain of uncertain etiology has been shown to improve the further clinical evaluation and outcomes of these patients. Conclusion: This review aims to summarize the main indications and techniques used in TRO protocols in EDs, and the role of TRO-CTA protocols in risk stratification of patients with acute chest pain.

Development of interventional methods has revolutionized the treatment of structural cardiac diseases. Given the complexity of structural interventions and the anatomical variability of various structural defects, novel imaging techniques have been implemented in the current clinical practice for guiding the interventional procedure and for selection of the device to be used. Three– dimensional echocardiography is the most used imaging method that has improved the threedimensional assessment of cardiac structures, and it has considerably reduced the cost of complications derived from malalignment of interventional devices. Assessment of cardiac structures with the use of angiography holds the advantage of providing images in real time, but it does not allow an anatomical description. Transesophageal Echocardiography (TEE) and intracardiac ultrasonography play major roles in guiding Atrial Septal Defect (ASD) or Patent Foramen Ovale (PFO) closure and device follow-up, while TEE is the procedure of choice to assess the flow in the Left Atrial Appendage (LAA) and the embolic risk associated with a decreased flow. On the other hand, contrast CT and MRI have high specificity for providing a detailed description of structure, but cannot assess the flow through the shunt or the valvular mobility. This review aims to present the role of modern imaging techniques in pre-procedural assessment and intraprocedural guiding of structural percutaneous interventions performed to close an ASD, a PFO, an LAA or a patent ductus arteriosus.

Bioresorbable Vascular Scaffolds (BVS) are polymer-based materials implanted in the coronary arteries in order to treat atherosclerotic lesions, based on the concept that once the lesion has been treated, the material of the implanted stent will undergo a process of gradual resorption that will leave, in several years, the vessel wall smooth, free of any foreign material and with its vasomotion restored. However, after the first enthusiastic reports on the efficacy of BVSs, the recently published trials demonstrated disappointing results regarding long-term patency following BVS implantation, which were mainly attributed to technical deficiencies during the stenting procedure. Intracoronary imaging could play a crucial role for helping the operator to correctly implant a BVS into the coronary artery, as well as providing relevant information in the follow-up period. This review aims to summarize the role of intracoronary imaging in the follow-up of coronary stents, with a particular emphasis on the role of intravascular ultrasound and optical coherence tomography for procedural guidance during stent implantation and also for follow-up of bioabsorbable scaffolds.

Introduction: Atrial Fibrillation (AF) is associated with remodeling of the atrial tissue, which leads to fibrosis that can contribute to the initiation and maintenance of AF. Delayed- Enhanced Cardiac Magnetic Resonance (DE-CMR) imaging for atrial wall fibrosis detection was used in several studies to guide AF ablation. The aim of present study was to systematically review the literature on the role of atrial fibrosis detected by DE-CMR imaging on AF ablation outcome. Methods: Eight bibliographic electronic databases were searched to identify all published relevant studies until 21st of March, 2016. Search of the scientific literature was performed for studies describing DE-CMR imaging on atrial fibrosis in AF patients underwent Pulmonary Vein Isolation (PVI). Results: Of the 763 citations reviewed for eligibility, 5 articles (enrolling a total of 1040 patients) were included into the final analysis. The overall recurrence of AF ranged from 24.4 - 40.9% with median follow-up of 324 to 540 days after PVI. With less than 5-10% fibrosis in the atrial wall there was a maximum of 10% recurrence of AF after ablation. With more than 35% fibrosis in the atrial wall there was 86% recurrence of AF after ablation. Conclusion: Our analysis suggests that more extensive left atrial wall fibrosis prior ablation predicts the higher arrhythmia recurrence rate after PVI. The DE-CMR imaging modality seems to be a useful method for identifying the ideal candidate for catheter ablation. Our findings encourage wider usage of DE-CMR in distinct AF patients in a pre-ablation setting.

Background: The central nervous system’s involvement in Rheumatoid Arthritis (RA) is infrequent and can be life-threatening. Mass-like CNS involvement is an unusual presentation. A 45 year old man had suffered seropositive rheumatoid arthritis for five years referred to our hospital with one-week history of right-sided facial paralysis, left hemiparesis and headache. Discussion: MRI demonstrated hyperintense mass-like lesion extended from mesencephalon to right hippocampus and basal ganglia on T2 and FLAIR images. On DWI, restricted diffusion was not present. After contrast administration, minimal contrast enhancement was noted. After methotrexate and steroid treatment, the size had been markedly shrunken on the follow-up images. The clinical symptoms were also improved. Conclusion: To our knowledge, the mass-like presentation was not reported in the literature. We report an unusual case of brain involvement of rheumatoid arthritis mimicked tumor.

Background: Although measles epidemic has been controlled effectively after measles vaccination being carried out, China is still the focus of measles epidemic. The lower respiratory tract infections (LRTIs) is the most common complication, and also the most common reason for the death of patients with measles. Purpose: To analyze what clinical factors could affect the grades of LRTIs in children under five years old with measles. Methods: Patients’ 13 clinical factors and chest radiography were analyzed retrospectively. Based on the chest radiography, the LRTIs were divided into 3 grades. The clinical factors and the grades of LRTIs were analyzed by ordered logistic regression analysis. Results: There were 74 cases in grade 0, 77 cases in grade 1, and 36 cases in grade 2. After univariate logistic regression analysis, there were 5 clinical factors whose P value were no more than 0.1, including the children’s course of disease before admission, co-infection other pathogens, vaccination, the first symptoms and gender. After ordinal logistic regression analysis, the difference in the course of disease before admission (OR = 1.134, 95% CI: 1.025 to 1.141), without vaccination (OR = 1.808, 95% CI: 1.065 to 3.065) and co-infected other pathogens other pathogens infections (OR = 1.618, 95% CI: 1.073 to 2.440) during different grades was statistically significant (P < 0.05). Conclusion: In our study, there were three clinical factors, including “with a long course of disease before admission”, “without measles vaccination” and “with other pathogens infections”, as the independent risk factors of the grades of LRTIs in children with measles.

Background: Image reconstruction of magnetic induction tomography (MIT) is a typical ill-posed inverse problem, which means that the measurements are always far from enough. Thus, MIT image reconstruction results using conventional algorithms such as linear back projection and Landweber often suffer from limitations such as low resolution and blurred edges. Methods: In this paper, based on the recent finite rate of innovation (FRI) framework, a novel image reconstruction method with MIT system is presented. Results: This is achieved through modeling and sampling the MIT signals in FRI framework, resulting in a few new measurements, namely, fourier coefficients. Because each new measurement contains all the pixel position and conductivity information of the dense phase medium, the illposed inverse problem can be improved, by rebuilding the MIT measurement equation with the measurement voltage and the new measurements. Finally, a sparsity-based signal reconstruction algorithm is presented to reconstruct the original MIT image signal, by solving this new measurement equation. Conclusion: Experiments show that the proposed method has better indicators such as image error and correlation coefficient. Therefore, it is a kind of MIT image reconstruction method with high accuracy.

Purpose: The purpose of this study was to investigate T1 relaxation time of the human Achilles tendon, to test its short-term repeatability as well as the minimal detectable change, and to assess the extent that correlate with clinical symptoms. Methods: Twenty asymptomatic volunteers and eighteen patients with clinically and sonographically confirmed tendinopathy were scanned for ankle using a 3 Tesla (T) MR scanner. T1 maps were calculated from a variable flip angle gradient echo Ultra-short echo time sequence (VFA-GE UTE) and inversion recovery spin echo sequence (IR-SE) using a self-developed matlab algorithm in three regions of interest of Achilles Tendon (AT). Signal to Noise Ratio (SNR) between the two sequences was evaluated. INTRA-class Correlation Coefficient (ICC), Coefficient of Variation (CV) and the Least Significant Change (LSC) were calculated, to test short-term repeatability of T1. Subjects were assessed by the VISA-A clinical score. P values less than 0.005 were considered statistically significant. Results: Mean T1 values were 427.09 ± 53.37 ms and 528.70 ± 103.50 ms using IR-SE sequence and 575.43 ± 110.60 ms and 875.81 ± 425.77 ms with VFA-GE UTE sequence in the whole AT for volunteers and patients, respectively. T1 values showed a significant difference between volunteers and patients (P=0.001). Regional variation of T1 in healthy and tendinopathic AT were greater for VFA-GE UTE sequence than for IR-SE sequence. VFA-GE UTE sequence showed clearly higher SNR compared to IR-SE sequence. Short-term repeatability of T1 values for volunteers showed an LSC of 22% and 14% for IR-SE sequence and VFA-GE UTE sequence, respectively. For patients, LSC was 14% and 5% for IR-SE sequence and VFA-GE UTE sequence, respectively. There was no correlation between T1 and VISA-A clinical score (p>0.005). Conclusion: VFA-GE UTE sequence used for T1 mapping calculation demonstrated short acquisition time and clearly high SNR. Results revealed that T1 relaxation time can be used as a biomarker to differentiate between healthy and pathologic Achilles tendon. However, T1 showed no correlation with the VISA-A clinical score.

Background: Thyroid nodules are a common clinical entity with high incidence. Ultrasound is often employed to detect and evaluate thyroid nodules. The development of an efficient automated method to detect thyroid nodules using ultrasound has the potential to reduce both physician workload and operator-dependence. Objectives: To study the method of automatic detection of thyroid nodules based on deep learning using ultrasound, and to obtain the detection method with higher accuracy and better performance. Methods: A total of 1200 ultrasound images of thyroid nodules and 800 ultrasound thyroid images without nodule are collected. An improved faster R-CNN based detection method of thyroid nodule is proposed. Instead of using VGG16 as the backbone, ResNet is employed as the backbone for faster R-CNN. SVM, CNN and Faster-RCNN methods are used for thyroid nodule detection test. Precision, sensitivity, specificity and F1-score indicators are used to evaluate the detection performance of different methods. Results: The method based on deep learning is superior to that based on SVM. Faster R-CNN method and the improved method are better than CNN method. Compared with VGG16 as the backbone, RestNet101 backbone based faster R-CNN method achieves better thyroid detection effect. From the accuracy index, the proposed method is 0.084, 0.032 and 0.019 higher than SVM, CNN and faster R-CNN, respectively. Similar results can be seen in precision, sensitivity, specificity and F1-Score indicators. Conclusion: The proposed method of deep learning achieves the best performance values with the highest true positive and true negative detection compared to other methods and performs best in the detection of thyroid nodules.