Current Medical Imaging - Volume 18, Issue 6, 2022

Background: Coronavirus (COVID-19) is a group of infectious diseases caused by related viruses called coronaviruses. In humans, the seriousness of infection caused by a coronavirus in the respiratory tract can vary from mild to lethal. A serious illness can be developed in old people and those with underlying medical problems like diabetes, cardiovascular disease, cancer, and chronic respiratory disease. For the diagnosis of coronavirus disease, due to the growing number of cases, a limited number of test kits for COVID-19 are available in the hospitals. Hence, it is important to implement an automated system as an immediate alternative diagnostic option to pause the spread of COVID-19 in the population. Objective: This paper proposes a deep learning model for the classification of coronavirus infected patient detection using chest X-ray radiographs. Methods: A fully connected convolutional neural network model is developed to classify healthy and diseased X-ray radiographs. The proposed neural network model consists of seven convolutional layers with the rectified linear unit, softmax (last layer) activation functions, and max-pooling layers which were trained using the publicly available COVID-19 dataset. Results and Conclusion: For validation of the proposed model, the publicly available chest X-ray radiograph dataset consisting of COVID-19 and normal patient’s images were used. Considering the performance of the results that are evaluated based on various evaluation metrics such as precision, recall, MSE, RMSE and accuracy, it is seen that the accuracy of the proposed CNN model is 98.07%.

Lung Ultrasound (LUS) has evolved considerably over the last few years. The aim of the current review is to conduct a systematic review reported from a number of studies to show the usefulness of (LUS) and point of care ultrasound for diagnosing COVID-19. A systematic search of electronic data was conducted, including the national library of medicine, and the national institute of medicine, PubMed Central (PMC), to identify the articles published on (LUS) to monitor COVID-19. This review highlights the ultrasound findings reported in articles before the occurrence of the pandemic (11), clinical articles before COVID-19 (14), review studies during the pandemic (27), clinical cases during the pandemic (5) and other varying aims articles. The reviewed studies revealed that ultrasound findings can be used to help in the detection and staging of the disease. The common patterns observed included irregular and thickened A-lines, multiple B-lines ranging from focal to diffuse interstitial consolidation, and pleural effusion. Sub-plural consolidation is found to be associated with the progression of the disease and its complications. Pneumothorax was not recorded for COVID-19 patients. Further improvement in the diagnostic performance of (LUS) for COVID-19 patients can be achieved by using elastography, contrast-enhanced ultrasound, and power Doppler imaging.

According to the International Agency for Research on Cancer (IARC), the mortality rate due to brain tumors is 76%. It is required to detect the brain tumors as early as possible and to provide the patient with the required treatment to avoid any fatal situation. With the recent advancement in technology, it is possible to automatically detect the tumor from images such as Magnetic Resonance Iimaging (MRI) and computed tomography scans using a computer-aided design. Machine learning and deep learning techniques have gained significance among researchers in medical fields, especially Convolutional Neural Networks (CNN), due to their ability to analyze large amounts of complex image data and perform classification. The objective of this review article is to present an exhaustive study of techniques such as preprocessing, machine learning, and deep learning that have been adopted in the last 15 years and based on it to present a detailed comparative analysis. The challenges encountered by researchers in the past for tumor detection have been discussed along with the future scopes that can be taken by the researchers as the future work. Clinical challenges that are encountered have also been discussed, which are missing in existing review articles.

Computed Tomography (CT) scanning generates 3-D images of the inside structures of the body by delivering a comparative radiation dose to the patient. This requires great concern of optimization via establishing Diagnostic Reference Level (DRL). DRL values can be estimated based on reference patient percentiles (such as 90th, 75th, and 50th) dose distribution. DRL has significant uses in professional judgments by generating harmonized evidence about the radiation dose received by the patient. The primary goal of this review is to assess the practical application of DRL in CT procedures internationally. The main objective of establishing DRLs is to optimize the patient dose without compromising the image quality in order to obtain adequate diagnostic information. That means the inescapability of DRL for a country in medical diagnosis is to reduce the limitation of dose dispersion, to harmonize and expand the good practice, to narrow large dispersion of doses, and to create systematic supervision for unwanted radiological doses. The review presents that international records have a wide range of mean dose distributions due to the variation of exam protocols and technical parameters in use. Hence, this review recommends that each CT health facility are required to exercise careful dose reduction strategies by accounting for adequate image quality with sufficient diagnostic information via follow-up of concerned bodies.

Background: Gadolinium Ethoxybenzyl Diethylenetriamine Pentaacetic Acid (Gd- EOB-DTPA) has become a widely used liver-specific contrast agent worldwide, but its value and limitations as a diagnostic technique with Hepatocellular Carcinoma (HCC), have not been assessed. Introduction: A review of the latest evidence available on the diagnostic value of Gd-EOB-DTPA- enhanced MRI for the evaluation of HCC is reported. Methods: A systematic, comprehensive literature search was conducted with PubMed, Scopus, EMBASE, the Web of Science, the Cochrane Library, CNKI, vip, wanfangdata and CBM from inception to June 31, 2020. The QUADAS-2 tool was used to evaluate the quality of the included studies. Pooled Sensitivity (SEN), Pooled Specificity (SPE), pooled positive likelihood ratio (PLR), pooled negative likelihood ratio (NLR), pooled diagnostic odds ratio (dOR) and summary receiver operating characteristic (SROC) curves were calculated to assess the diagnostic value of the individual diagnostic tests. Results: A total of 47 articles were included, involving a total of 6362 nodules in 37 studies based on per-lesion studies. There were 13 per-patient studies, including a total of 1816 patients. The results of the meta-analysis showed that the per-lesion studies pooled weighted values were SEN 0.90 [95% confidence interval (CI): 0.87-0.92], SPE 0.92 (95% CI: 0.90-0.94), PLR 11.6 (95% CI: 8.8-15.2), NLR 0.11 (95% CI: 0.09-0.14) and dOR 107.0 (95% CI: 74.0-155.0). The AUC of the SROC curve was 0.96. The per-patient studies pooled weighted values were SEN 0.84 [95% confidence interval (CI): 0.78-0.89], SPE 0.92 (95% CI: 0.88-0.94), PLR 10.4 (95% CI: 7.4-14.6), NLR 0.17 (95% CI: 0.12-0.24) and dOR 61.0 (95% CI: 42.0-87.0). The AUC of the SROC curve was 0.95 and subgroup analyses were performed. Conclusion: The diagnostic value of Gd-EOB-DTPA for HCC was quantitatively evaluated in a per-lesion study and a per-patient study using a systematic review of the literature. A positive conclusion was drawn: Gd-EOB-DTPA-enhanced imaging is a valuable diagnostic technique for HCC. The size of the nodules and the selection of the imaging diagnostic criteria may affect the diagnostic sensitivity.

Background: Different molecular breast cancer subtypes present different biologic features, treatment options, and clinical prognoses. The breast cancer imaging phenotype may help precisely classify breast cancer in a non-invasive manner. Objective: To identify the association between the imaging and clinicopathologic features of invasive breast cancer according to the molecular subtype. Methods: We retrospectively reviewed the electronic medical records of 313 consecutive women with breast cancer who underwent surgery between March 2018 and February 2019. Preoperative imaging studies were also reviewed and the association between the clinicopathologic and imaging features was evaluated according to the molecular subtype. Results: On mammography, the presence of microcalcifications was correlated with the human epidermal factor receptor 2-positive subtype (67%, 14/21). Luminal A and B tumors were more likely to have a spiculated margin (57% [63/110] and 41% [34/81]), while human epidermal factor receptor 2-positive and triple-negative breast cancers were more likely to have an indistinct margin (56% [10/18] and 35% [17/48]). On ultrasonography, luminal A tumors were likely to be depicted as masses with an irregular shape (85%, 115/136) and spiculated margin (49%, 66/136). On magnetic resonance imaging, triple-negative breast cancer appeared as a mass (n=13) that frequently had an irregular shape (62%, 8/13) but was more likely to be oval or round (39%, 5/13) than other subtypes. Conclusion: Some imaging features on mammography, ultrasonography, and magnetic resonance imaging could be useful predictors of the molecular subtype of breast cancer and may aid precision medicine development for patients with breast cancer according to the subtype.

Aim: This study aimed to investigate whether initial chest Computed Tomography (CT) findings of COVID-19 patients could predict clinical outcomes, prognoses, and mortality rates associated with the infection. Background: Published studies on chest CT in COVID-19 infection do not go beyond describing the characteristics of the current period. Comparative analysis of chest CT findings upon hospital admission among patients with different clinical outcomes is scarce. Objective: We sought to retrospectively evaluate and compare clinical outcomes, prognoses, and mortality rates based upon the initial chest CT findings of 198 consecutive symptomatic patients with COVID-19 confirmed by Polymerase Chain Reaction (PCR). Methods: Patients (N = 198) were divided into three groups according to their clinical outcomes as follows: group 1 (n = 62) included patients discharged from the service, group 2 (n= 60) included patients hospitalized in the intensive care unit, and group 3 (n = 76) included patients who died despite treatment. Results: Predictors of poor prognosis and mortality with regard to chest CT findings included mediastinal lymphadenopathy, pleural effusion, and pericardial effusion, and clinical characteristics of age, dyspnea, and hypertension. The halo sign on chest CT was a good prognosis predictor in multivariate analysis. Conclusion: Some CT findings, such as discharge, intensive care unit hospitalization, and death as the worst consequence, significantly correlated with endpoints. These findings support the role of CT imaging for potentially predicting clinical outcomes of patients with COVID-19.

Background: Obesity is one of the major public health problems globally, especially among women. Obesity is associated with glaucoma, cataract, age-related macular degeneration and diabetic retinopathy. Although it is clear that the anatomy and physiologic functions of the choroid may be affected by obesity, data investigating the effect of obesity on the choroid is limited and/or unavailable for the Saudi population. Objective: To assess Choroidal Thickness (CT) changes in a sample of healthy Saudi Arabian women with different Body Mass Index (BMI) using Spectral-domain Ocular Coherence Tomography (SD-OCT). Methods: A total of 140 healthy women aged 18-29 years (mean age ± standard deviation SD, 24.5 ± 1.7 years) with different BMI, axial length (AL) ≤ 24 ± 1.0 mm, and spherical equivalent refraction (SER) of ≤ ±2.0 dioptres were enrolled for the study. The participants were age and refractionmatched, and grouped into underweight (BMI ≤ 18.0 kg/m2) (n = 30), normal (control group) (18.5–24.9 kg/m2) (n = 43), overweight (25.0–29.9 kg/m2) (n=37), and obese study groups (≥ 30.0 kg/m2) (n = 30). SD-OCT imaging was performed on one eye of each participant. Comparisons among groups for all locations and the associations between CT and other variables were examined. Results: The mean CT at the subfoveal region (285 ± 31 μm, range: 203 μm to 399 μm) was significantly greater, and it was the lowest in the nasal region (248 ± 26 μm, range 154 to 304) compared with other locations, across all the groups (p < 0.05). Compared with the control, the subfoveal choroid was thinner in the obese group (mean difference: 22.6 μm, 95% Confidence Interval; CI: 8.6 μm to 36.6 μm; p = 0.02) and across all locations (p < 0.05) but thicker at the temporal location in the underweight group (12.4 μm, 95% CI: -23.7 μm to −1.04 μm; p = 0.01). No significant association of subfoveal CT with any of the measured parameters, including age (p-values ranged from 0.10 to 0.90), was found. Conclusion: BMI may have an influence on the CT of healthy individuals and could be a cofounder in research studies on CT. It is, therefore, recommended that BMI should be evaluated in the clinical diagnosis and management of conditions associated with choroid in healthy individuals.

Background: The scapula is a small irregular-shaped flat bone, which may suffer from a variety of tumors or tumor-like lesions. As the imaging manifestations are complex and changeable, correct imaging diagnosis is difficult. Introduction: At present, there are few related radiology literatures, and it is necessary to fully analyze the imaging signs of different types of benign and malignant tumors in scapula to guide clinical treatment. This study was to investigate clinical and imaging presentations of tumors and tumor- like lesions in the scapula so as to increase the diagnostic accuracy of diseases in the scapula. Methods: Patients with scapular tumors confirmed by pathology were enrolled. The imaging and clinical data were analyzed. Results: Among 108 patients, benign tumors were in 53 (49.1%) cases, intermediate in seven (6.5%), and malignant in 48 (44.4%) involving 16 diseases. Osteochondroma was the first benign tumors in 45 cases accounting for 84.9% of all benign scapular tumors, followed by chondroma in four cases (7.5%). The intermediate tumors were mainly eosinophilic granuloma in four cases. Metastatic tumors were the commonest malignant tumor (27 cases or 56.2% of all malignant tumors), followed by chondrosarcoma (in 13 cases). Except for the one case of chondroblastoma in which the lesion involved the glenoid cavity, all the other cartilaginous tumors were located in the scapular body and processes. The type of lesions in the bony processes is the same as in the scapular body, the common lesions in the central area of the body were malignant tumors, and the commonest lesions in the glenoid area were metastasis. Common imaging features of malignant scapular tumors were ill-defined margins, cortical destruction and soft tissue involvement. The imaging features of chondrosarcoma lack specificity except for calcification. Benign lesions usually had a clear boundary and marginal sclerosis. Conclusion: A wide variety of benign and malignant tumors may occur in the scapula with mostly cartilaginous and metastatic tumors, and the location and distribution of lesions are similar in the scapula to those in the long bones.

Introduction: Metaplastic breast carcinoma is an uncommon malignancy that constitutes < 5% of all breast cancers. There are 5 subtypes which are spindle cell, squamous cell, carcinosarcoma, matrix-producing and metaplastic with osteoclastic giant cells. Spindle cell carcinoma represents approximately <0.3% of invasive breast carcinomas. It is typically a triple-negative cancer with distinct pathological characteristics, but relatively a non-conclusive on imaging findings. Case Report: An elderly lady presented with an enlarging painful left breast lump for one year. Palpable left breast lump was found on clinical examination. Mammography demonstrated a high density, oval lesion with a partially indistinct margin. Corresponding ultrasound showed a large irregular heterogeneous lesion with solid-cystic areas. Histopathology showed atypical spindle-shaped cells that stained positive for cytokeratins and negative for hormone and human epidermal growth factor receptors, which favoured spindle cell metaplastic carcinoma. Left mastectomy and axillary dissection were performed, and the final diagnosis was consistent with metaplastic spindle cell carcinoma. Conclusion: Spindle cell carcinoma of the breast is a rare and aggressive histological type of carcinoma, which may present with benign features on imaging. Tissue diagnosis is essential for prompt diagnosis with multidisciplinary team discussion to guide management and improve patient’s outcomes.

Introduction: Torsion of the falciform ligament, one of the rarest causes of acute abdominal pain, often presents with pain in the right upper quadrant and epigastrium. Case Presentation: In this case, we present the Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) findings of torsion of the falciform ligament that occurred in the presence of omental fat herniation through the foramen of Morgagni in an 88-year-old female patient who presented to the emergency department with acute epigastric pain. Conclusion: Torsion of the falciform ligament may develop secondary to omental hernia in the setting of Morgagni hernia and should be taken into consideration as one of the rarest causes of acute abdominal pain, even in elderly patients.