Advances In Medical Imaging Research Articles

Thoracic surgery in Hong Kong.

In the era of modernized medicine, thoracic surgery has been focusing on achieving minimally invasive surgery and providing a one-stop solution in treating thoracic diseases. Particularly in the Asia population, where patients are keen to have smaller wound and shorter hospital stay, thoracic surgery in Hong Kong has evolved from the traditional open thoracotomy approach to video-assisted thoracoscopic surgery (VATS). In our institution, uniportal VATS for major lung resection was developed in 2012. While uniportal VATS has brought advantages into managing thoracic pathologies, it also brought challenges like instrument fencing during manipulation and suboptimal visualization angle. To improve the procedure and its outcomes, novel techniques and equipment have been developed, for example, double-hinged instruments, robotic assisted technology and magnetic anchored and guided endoscopes (MAGS). With advanced medical imaging nowadays, management of small lung nodules or ground glass opacity (GGO) is in higher demand than ever before. Our hybrid operating room (HOR) can incorporate instant and real-time imaging in lesion localization, and provide treatment via VATS or electromagnetic navigated bronchoscopic (ENB) ablation in a one-stop manner. This paper will review the literature related to the historical development and clinical outcomes of thoracic surgery in Hong Kong and discuss the future perspective of ongoing development.

Evaluation of Advanced Medical Imaging Services at Government Hospitals-West Bank

Background: Medical imaging services provided to patients in the CT and MRI unit are essential to reach the best results for assessing their health conditions. Objective: The aim of this study was to evaluate the client’s satisfaction and medical services of the CT and MRI at private centres and hospitals in the West Bank- Palestine. Methods: The study was based on triangulated design; checklist, interview and questionnaire. The checklist is made by researchers to evaluate CT and MRI units’ design. The researchers interviewed 100 patients who were imaged in CT and MRI units to assess their satisfaction with the provided medical service. The questionnaire was distributed to 28 radiologic technologists (RTs) to know their characteristics and to assess the extent of the RTs commitment to the medical services. Results: Findings revealed that from the client’s perspective: Inferential analysis shows that there was a statistically significant difference at the level of significant α≤0.05 in reception and waiting with respect to the residence. While there is no statistically significant difference at (α≤0.05) in the evaluating of reception and communication in the radiology department with respect to gender and employment status. Meanwhile, the results showed there is a relationship between satisfaction and the monthly income of participants. The study showed MRI units track the international standard system in structures and occupational safety while about 87.5% of CT units follow occupational safety and about 65% of the structures. Conclusion: Through the study, the shortage in the CT and MRI units, and RTs compared to other countries became clear. The deficiency was observed in radiological protection techniques presented to patients and RTs

Functional and Metabolic Imaging in Heart Failure with Preserved Ejection Fraction: Promises, Challenges, and Clinical Utility

Heart failure with preserved ejection fraction (HFpEF) is recognised as an increasingly prevalent, morbid and burdensome condition with a poor outlook. Recent advances in both the understanding of HFpEF and the technological ability to image cardiac function and metabolism in humans have simultaneously shone a light on the molecular basis of this complex condition of diastolic dysfunction, and the inflammatory and metabolic changes that are associated with it, typically in the context of a complex patient. This review both makes the case for an integrated assessment of the condition, and highlights that metabolic alteration may be a measurable outcome for novel targeted forms of medical therapy. It furthermore highlights how recent technological advancements and advanced medical imaging techniques have enabled the characterisation of the metabolism and function of HFpEF within patients, at rest and during exercise.

The Key Role of Magnetic Resonance Imaging in the Detection of Neurodegenerative Diseases-Associated Biomarkers: A Review.

Neurodegenerative diseases (NDs), including chronic disease such as Alzheimer's disease, Parkinson's disease, Huntington's disease, and multiple sclerosis, and acute diseases like traumatic brain injury and ischemic stroke are characterized by progressive degeneration, brain tissue damage and loss of neurons, accompanied by behavioral and cognitive dysfunctions. So far, there are no complete cures for NDs; thus, early and timely diagnoses are essential and beneficial to patients' treatment. Magnetic resonance imaging (MRI) has become one of the advanced medical imaging techniques widely used in the clinical examination of NDs due to its non-invasive diagnostic value. In this review, research published in English in current decade from PubMed electronic database on the use of MRI to detect specific biomarkers of NDs was collected, summarized, and discussed, which provides valuable suggestions for the early diagnosis, prevention, and treatment of NDs in the clinic.

Systematic Review: Incidence of Pheochromocytoma and Paraganglioma Over 70 Years.

ContextPheochromocytomas and paragangliomas (PPGLs) are known to be rare. However, there is scant literature reporting their epidemiology, particularly whether the diagnosis of PPGL has increased with advances in medical imaging and biochemical and genetic testing.ObjectiveThe primary objective of this systematic review was to determine the annual incidence of PPGLs and change over time.DesignA systematic review was performed. Medline, Embase, PubMed, and Web of Science Core Collection databases were searched to identify studies reporting PPGL incidence. Studies were eligible for inclusion from the database’s inception until August 30, 2021.ResultsA total of 6109 manuscripts were identified; 2282 duplicates were excluded, and a further 3815 papers were excluded after abstract and/or full text review. Twelve studies were included in the final review. The incidence of PPGL ranged from 0.04 to 0.95 cases per 100 000 per year. Incidence increased over time, from approximately 0.2/100,000 individuals in studies performed before 2000, to approximately 0.6/100,000 in studies undertaken after 2010. The mode of diagnosis changed over the same time period, with more patients diagnosed from incidental imaging findings, and fewer at autopsy or from symptoms.ConclusionThe annual incidence of PPGL has increased over time. Much of this increase is likely from incidental identification of tumors on imaging. However, the epidemiology of PPGL remains understudied, in particular, in associations with altitude, ethnicity, and genetics. To improve early detection and management guidelines, these gaps should be addressed.

All-Around Real Label Supervision: Cyclic Prototype Consistency Learning for Semi-Supervised Medical Image Segmentation.

Semi-supervised learning has substantially advanced medical image segmentation since it alleviates the heavy burden of acquiring the costly expert-examined annotations. Especially, the consistency-based approaches have attracted more attention for their superior performance, wherein the real labels are only utilized to supervise their paired images via supervised loss while the unlabeled images are exploited by enforcing the perturbation-based "unsupervised" consistency without explicit guidance from those real labels. However, intuitively, the expert-examined real labels contain more reliable supervision signals. Observing this, we ask an unexplored but interesting question: can we exploit the unlabeled data via explicit real label supervision for semi-supervised training? To this end, we discard the previous perturbation-based consistency but absorb the essence of non-parametric prototype learning. Based on the prototypical networks, we then propose a novel cyclic prototype consistency learning (CPCL) framework, which is constructed by a labeled-to-unlabeled (L2U) prototypical forward process and an unlabeled-to-labeled (U2L) backward process. Such two processes synergistically enhance the segmentation network by encouraging morediscriminative and compact features. In this way, our framework turns previous "unsupervised" consistency into new "supervised" consistency, obtaining the "all-around real label supervision" property of our method. Extensive experiments on brain tumor segmentation from MRI and kidney segmentation from CT images show that our CPCL can effectively exploit the unlabeled data and outperform other state-of-the-art semi-supervised medical image segmentation methods.

Multimodal medical image fusion with convolution sparse representation and mutual information correlation in NSST domain

Multimodal medical image is an effective method to solve a series of clinical problems, such as clinical diagnosis and postoperative treatment. In this study, a medical image fusion method based on convolutional sparse representation (CSR) and mutual information correlation is proposed. In this method, the source image is decomposed into one high-frequency and one low-frequency sub-band by non-subsampled shearlet transform. For the high-frequency sub-band, CSR is used for high-frequency coefficient fusion. For the low-frequency sub-band, different fusion strategies are used for different regions by mutual information correlation analysis. Analysis of two kinds of medical image fusion problems, namely, CT–MRI and MRI–SPECT, reveals that the performance of this method is robust in terms of five common objective metrics. Compared with the other six advanced medical image fusion methods, the experimental results show that the proposed method achieves better results in subjective vision and objective evaluation metrics.

Thrifty Neural Architecture Search for Medical Image Segmentation (Student Abstract)

Convolutional neural network (CNN) based image segmentation has been widely used in analyzing medical images and benefited many real-world disease diagnosis applications. However, existing advanced CNN-based medical image segmentation models usually contain numerous parameters that require massive computation and memory, limiting the applicability of these models in the data-constrained or hardware-constrained environments. By leveraging the recently proposed neural architecture search (NAS), this paper presents a novel approach, dubbed Thrifty NAS, to design computation and memory-efficient models for medical image segmentation automatically. The searched models by Thrifty NAS are with much fewer parameters while retaining competitive performance. More specifically, we design a micro level space for cell structure search and a macro level cell path for better network structure modeling. Extensive experimental results in different medical image datasets verify the effectiveness of the proposed method with competitive segmentation performance, especially with minuscule neural architecture model size, i.e., 0.61M that is superior to U-Net (7.76 M) and UNet++ (9.04 M).

Precision medical image hash retrieval by interpretability and feature fusion

Background and Objective: To address the problem of low accuracy of medical image retrieval due to high inter-class similarity and easy omission of lesions, a precision medical image hash retrieval method combining interpretability and feature fusion is proposed, taking chest X-ray images as an example.Methods: Firstly, the DenseNet-121 network is pre-trained on a large dataset of medical images without manual annotation using the comparison to learn (C2L) method to obtain a backbone network model containing more medical representations with training weights. Then, a global network is constructed by using global image learning to acquire an interpretable saliency map as attention mechanisms, which can generate a mask crop to get a local discriminant region. Thirdly, the local discriminant regions are used as local network inputs to obtain local features, and the global features are used with the local features by dimension in the pooling layer. Finally, a hash layer is added between the fully connected layer and the classification layer of the backbone network, defining classification loss, quantization loss and bit-balanced loss functions to generate high-quality hash codes. The final retrieval result is output by calculating the similarity metric of the hash codes.Results: Experiments on the Chest X-ray8 dataset demonstrate that our proposed interpretable saliency map can effectively locate focal regions, the fusion of features can avoid information omission, and the combination of three loss functions can generate more accurate hash codes. Compared with the current advanced medical image retrieval methods, this method can effectively improve the accuracy of medical image retrieval.Conclusions: The proposed hash retrieval approach combining interpretability and feature fusion can effectively improve the accuracy of medical image retrieval which can be potentially applied in computer-aided-diagnosis systems.

Modern Diagnostic Imaging Technique Applications and Risk Factors in the Medical Field: A Review.

Medical imaging is the process of visual representation of different tissues and organs of the human body to monitor the normal and abnormal anatomy and physiology of the body. There are many medical imaging techniques used for this purpose such as X-ray, computed tomography (CT), positron emission tomography (PET), magnetic resonance imaging (MRI), single-photon emission computed tomography (SPECT), digital mammography, and diagnostic sonography. These advanced medical imaging techniques have many applications in the diagnosis of myocardial diseases, cancer of different tissues, neurological disorders, congenital heart disease, abdominal illnesses, complex bone fractures, and other serious medical conditions. There are benefits as well as some risks to every imaging technique. There are some steps for minimizing the radiation exposure risks from imaging techniques. Advance medical imaging modalities such as PET/CT hybrid, three-dimensional ultrasound computed tomography (3D USCT), and simultaneous PET/MRI give high resolution, better reliability, and safety to diagnose, treat, and manage complex patient abnormalities. These techniques ensure the production of new accurate imaging tools with improving resolution, sensitivity, and specificity. In the future, with mounting innovations and advancements in technology systems, the medical diagnostic field will become a field of regular measurement of various complex diseases and will provide healthcare solutions.

Imaging: New Frontiers in Vascular Training.

Advances in medical imaging have redefined the practice of vascular surgery. Current training programs for vascular surgery do not incorporate formal training in vascular imaging other than in duplex ultrasound when a physician is undergoing the vascular interpretation certification process. Yet imaging modalities and techniques have grown exponentially in the adjacent fields of interventional radiology, interventional and diagnostic cardiology, and neuroradiology, so much so that advanced imaging fellowships have been established in these fields. This article reviews the current state of vascular imaging training, identifies gaps in the current training regimen, and proposes an advanced vascular imaging fellowship for the future.

Alteration of Consciousness by Anaesthetics: A Multiscale Modulation from the Molecular to the Systems Level

General anaesthesia has been used in medical practice since the mid-nineteenth century, but its pharmacological mechanism of action is still not entirely clear. In a top-down approach, investigations probe smaller and smaller scales to shed light on how anaesthetics disrupt or alter neural activity, ultimately resulting in loss of consciousness. In the past few decades, advances in neuroscience and molecular biology allowed for investigations on the brain structure and function from the behavioural level to the systems, cellular, and molecular level. This multiscale approach implicates the molecular domain as a fundamental link between general anaesthesia and consciousness, which also sheds light on how anaesthetic agents affect the pathogenesis of postoperative behavioural changes. This review discusses the current state of knowledge about the relationship between consciousness and general anaesthesia determined using pharmacokinetics, molecular biology, and advanced medical imaging, including EEG, fMRI, PET, MEG. It is hoped that the mechanisms of action of anaesthetic gases may help solve the mystery of consciousness. Conversely, understanding the cellular and molecular mechanisms of consciousness could lead to the design and development of new anaesthetic agents and technologies to controllably turn off and on consciousness. It could also generate new concepts in neurocognitive pathophysiology disorders.

Imaging appearance of Ciliated Hepatic Cyst

Ciliated hepatic cyst is a benign, solitary, and rare lesion. It was described in 1857 by Friederich but its current name dates from 1984. Diagnosis of Ciliated hepatic cyst can be difficult because they are often asymptomatic and, in rare cases, may progress to a malignant tumor. The definitive diagnosis is based on histological examination. Since the advent of imaging, especially magnetic resonance imaging, diagnosis has become easier and easier. Most of the published cases have been published in the last 20 years by advances in medical imaging. We report here a case of ciliated hepatic foregut cyst observed on ultrasound, on computed tomography, and on magnetic resonance imaging in a 41-year-old woman.

FastMRI+, Clinical pathology annotations for knee and brain fully sampled magnetic resonance imaging data

Improving speed and image quality of Magnetic Resonance Imaging (MRI) using deep learning reconstruction is an active area of research. The fastMRI dataset contains large volumes of raw MRI data, which has enabled significant advances in this field. While the impact of the fastMRI dataset is unquestioned, the dataset currently lacks clinical expert pathology annotations, critical to addressing clinically relevant reconstruction frameworks and exploring important questions regarding rendering of specific pathology using such novel approaches. This work introduces fastMRI+, which consists of 16154 subspecialist expert bounding box annotations and 13 study-level labels for 22 different pathology categories on the fastMRI knee dataset, and 7570 subspecialist expert bounding box annotations and 643 study-level labels for 30 different pathology categories for the fastMRI brain dataset. The fastMRI+ dataset is open access and aims to support further research and advancement of medical imaging in MRI reconstruction and beyond.

Inter-Observer and Intra-Observer Variability in Gross Tumor Volume Delineation of Primary Esophageal Carcinomas Based on Different Combinations of Diagnostic Multimodal Images

Background and PurposeThis study aimed to investigate inter-/intra-observer delineation variability in GTVs of primary esophageal carcinomas (ECs) based on planning CT with reference to different combinations of diagnostic multimodal images from endoscopy/EUS, esophagography and FDG-PET/CT.Materials and MethodsFifty patients with pathologically proven thoracic EC who underwent diagnostic multimodal images before concurrent chemoradiotherapy were enrolled. Five radiation oncologist independently delineated the GTVs based on planning CT only (GTVC), CT combined with endoscopy/EUS (GTVCE), CT combined with endoscopy/EUS and esophagography (X-ray) (GTVCEX), and CT combined with endoscopy/EUS, esophagography, and FDG-PET/CT (GTVCEXP). The intra-/inter-observer variability in the volume, longitudinal length, generalized CI (CIgen), and position of the GTVs were assessed.ResultsThe intra-/inter-observer variability in the volume and longitudinal length of the GTVs showed no significant differences (p>0.05). The mean intra-observer CIgen values for all observers was 0.73 ± 0.15. The mean inter-observer CIgen values for the four multimodal image combinations was 0.67 ± 0.11. The inter-observer CIgen for the four combined images was the largest, showing significant differences with those for the other three combinations. The intra-observer CIgen among different observers and inter-observer CIgen among different combinations of multimodal images showed significant differences (p<0.001). The intra-observer CIgen for the senior radiotherapists was larger than that for the junior radiotherapists (p<0.001).ConclusionFor radiation oncologists with advanced medical imaging training and clinical experience, using diagnostic multimodal images from endoscopy/EUS, esophagography, and FDG-PET/CT could reduce the intra-/inter-observer variability and increase the accuracy of target delineation in primary esophageal carcinomas.

Effective of Modern Techniques on Content-Based Medical Image Retrieval: A Survey

The advancement in medical imaging has resulted in a rapid and large increase in medical images inside repositories. These medical images contain very important information that can be used in many things, including diagnosing diseases. This implies that a precise, efficient way of indexing and retrieving biomedical images is necessary to obtain medical images from such repositories in real-time. CBMIR, therefore, played an important part, where the CBMIR’s area is very important in the field of image processing and involves low-level feature extraction and similarity measures for the comparison of medical images such as color histograms, edges, texture, shape. The majority of the methods already in use in CBMIR enhance the retrieval of a medical image and diseases diagnosis by reducing the issue of the semantic gap between low visual and high semantic levels. Also, secure access to the medical image of diverse cases, which are often kept on a network and are susceptible to malicious attacks is considered an important target for all medical practitioners. So, most CBMIRs try to cover this target for the purpose of privacy preservation. So, in this survey, the most advanced (CBMIR) frameworks that were used to reduce the issue of semantic gaps, high dimensionality feature maps were covered, disease diagnosis, and medical image security. Furthermore, the different publicly and standard databases used in measuring the performance of these frameworks also were covered.

A Survey of Awareness of Parents and Caretakers on Diagnostic Radiological Examination Related Radiation Exposure in a Tertiary Hospital in Malaysia.

Background: With the advancement in medical imaging, radiological application in the paediatric population has also increased. Children, generally more radiosensitive, have a higher risk of developing certain malignancies. Therefore, this may result in uneasiness among parents and caretakers when their children need to undergo medical imaging examination. Hence, this study aims to assess the awareness of parents’ and caretakers’ awareness of medical imaging-related radiation exposure in our institution and their opinion of a medical radiation exposure-tracking programme for the paediatric population. Methodology: A cross-sectional survey was conducted for 6 months duration among parents and caretakers, who brought their children (under 12 years old) for imaging. The questionnaire booklet had eleven knowledge-based questions to assess respondents on ionising radiation-associated medical imaging, the radiation-related risk and radiation safety precaution. Results: Two hundred and fifteen respondents participated in this survey. More than 40% of the respondents failed to identify various dose-saving and ionising radiation-related imaging methods. Only 87 participants (40.5%) could correctly answer at least six out of eleven knowledge-based questions. Moreover, 88.4% of the respondents support a medical radiation exposure-tracking programme for their children. Conclusion: Parents and caretakers who visited our institution had inadequate awareness of medical radiation exposure. Appropriate measures need to be taken to address this promptly. Implementation of a medical radiation exposure-tracking programme for the paediatric population is considered timely as most respondents agree with this programme.

Education in Radiation Oncology-Current Challenges and Difficulties.

The evolution and development of radiotherapy in the last two decades has meant that postgraduate medical training has not kept up with this rapid progress both in terms of multidisciplinary clinical approaches and especially in terms of technological advances. Education in radiation oncology is a major priority in the context of the rapid development of radiotherapy, including advanced knowledge of radiobiology, radiation physics and clinical oncology, anatomy, tumor biology and advanced medical imaging. In this context, the lack of training in radiation oncology in the curricula of medical faculties may have detrimental consequences for the training of residents in radiotherapy but also in their choice of specialty after completing their university studies. There is a clear gap between resident physicians’ actual and required knowledge of radiotherapy, and this requires urgent remediation. In the context of technical advances in imaging-guided radiotherapy (IGRT) and new radiobiology data, a balanced approach divided equally between general oncology, clinical radiation oncology, radiation oncology technology, medical physics and radiobiology, anatomy and multimodal imaging, including mentorship could bring educational and career choice benefits for students of radiation oncology.

Year-end academic review of 2021: Advances in the field of birth defect prevention and control in China as of 2021

Year-end academic review of 2021: Advances in the field of birth defect prevention and control in China as of 2021

Evolutionary profile of pyonephrosis after surgical treatment, about 23 cases

ObjectivesTo describe the evolving profile of pyonephrosis after surgical treatment, identifying their epidemiological, clinical, paraclinical, and therapeutic aspects. Materials and methodsDescriptive retrospective study spread over a period of 5 years (2015–2019) including patients with pyonephrosis in the urology department. Results23 cases of pyonephrosis were collected. The average age of patients was 49 years (27–71 years), with male predominance (69.56%). It was found that the main element of the patient's medical history was urolithiasis (57%). Lower back pain is the main sign found in (96%) of cases, followed by infectious agents found in (42%) and a large kidney (21%). Renal ultrasound allowed us to evoke the diagnosis in 41% of cases and urine CT scan confirmed diagnosis in the majority of cases. The etiology was lithiasis in 78.26% of cases. Cytobacteriological urine examination (CEBU) isolated germs in 15 patients (65.21%) predominance of Escherichia coli in 7 cases (30.43%). The treatment included a nephrectomy preceded by a Subcutaneous nephrovesical bypass in 21 patients. The outcome was reassuring in 70.7% of cases, the main complications were parietal suppuration (30.43%), followed by chronic kidney failure (8.69%), enteroenteric fistula (4.34%), and digestive fistula (4.34%). The mortality was (8.69%). ConclusionPyonephrosis is a condition that is becoming increasingly rare. The reduction of its incidence may be related to recent advances in medical imaging which allow early diagnosis of causative conditions and their treatment.