Current Medical Imaging - Volume 18, Issue 3, 2022

The highly contagious novel Coronavirus Disease 2019 (COVID-19) broke out at the end of 2019 and has lasted for nearly one year, and the pandemic is still rampant around the world. The diagnosis of COVID-19 is on the basis of the combination of epidemiological history, clinical symptoms, and laboratory and imaging examinations. Among them, imaging examination is of importance in the diagnosis of patients with suspected clinical cases, the investigation of asymptomatic infections and family clustering, the judgment of patient recovery, rediagnosis after disease recurrence, and prognosis prediction. This article reviews the research progress of CT imaging examination in the COVID-19 pandemic.

Background: Background: Small Bowel Obstruction (SBO) accounts for 15% of abdominal pain complaints referred to emergency departments and imposes significant financial burdens on the healthcare system. The most common symptom and sign of SBO is the absence of stool or flatus passsage and abdominal distension, respectively. Patients who do not demonstrate severe clinical or imaging findings are typically treated with conservative approaches. Patients with clinical signs of sepsis or physical findings of peritonitis are often instantly transferred to the operating room without supplementary imaging assessment. However, in cases where symptoms are non-specific or physical examination is challenging, such as in cases with loss of consciousness, the diagnosis can be complicated. This paper discusses the key findings identifiable on Computed Tomography (CT) which are vital for the emergent triage, proper treatment and appropriate decision making in patients with suspected SBO. Methods: Narrative review of the literature. Results: CT plays a key role in emergent triage, proper treatment and decision making and provides high sensitivity, specificity, and accuracy in the detection of early-stage obstruction and acute intestinal vascular compromise. CT can also differentiate between various etiologies of SBO entity which is considered an important criterion in the triage of patients into surgical vs. non-surgical treatment. Conclusion: There Key CT findings which may suggest a need for surgical treatment include mesenteric edema, lack of the small-bowel feces, bowel wall thickening, fat stranding in the mesentery, and intraperitoneal fluid which are predictive of urgent surgical exploration.

T2/FLAIR hyperintensity in the mesial temporal lobe is the most common MR finding of herpes simplex encephalitis, but may be observed in other infectious and non-infectious diseases. The former includes herpes human virus 6 encephalitis, Japanese encephalitis, and neurosyphilis, and the latter autoimmune encephalitis, gliomatosis cerebri, bilateral or paradoxical posterior cerebral artery infarction, status epilepticus, and hippocampal sclerosis. Thus, T2/FLAIR hyperintensity in the mesial temporal lobe is not a disease-specific magnetic resonance imaging finding, and these conditions must be differentiated to ensure proper treatment. We review diseases that present with T2/FLAIR hyperintensity in the mesial temporal lobe and provide a helpful flow chart based on clinical and radiologic features.

Background: Cystic Renal Cell Carcinoma (CRCC) is often difficult to differentiate from complex cysts with sonographic manifestations of renal carcinoma. Contrast-Enhanced Ultrasound (CEUS) is a new technology, and its clinical utility in the diagnosis of renal cystic mass has not been established. Objective: The objective of this study is to analyze the characteristics of CEUS of renal cystic masses and to explore the clinical significance and value of CEUS in the diagnosis of CRCC. Methods: This study was a retrospective study. A total of 32 cystic masses from January 2018 to December 2019 were selected. The images of conventional Ultrasound (US) and CEUS were confirmed via surgical pathology. Routine US was used to observe the location, shape, size, boundary, cyst wall, internal echo, and blood supply of each cystic mass. CEUS observed contrast enhancement of the cyst wall, cystic septa, and solid nodules of cystic masses. Results: There were 26 cases of CRCC, 5 cases of renal cysts, and 1 case of renal tuberculosis. The enhancement pattern, degree of enhancement, and pseudocapsular sign by CEUS in benign and malignant masses had statistically significant differences (P<.05). In the diagnosis of CRCC, the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 92.3%, 83.3%, 90.6%, 96.0%, and 71.4% for CEUS; 57.6%, 66.7%, 59.3%, 88.2%, and 26.7% for conventional US, respectively. CEUS had a higher sensitivity and accuracy than the conventional US (P<.05), although the diagnostic specificity, positive predictive value and negative predictive value of the two methods were not significantly different (P>.05). Conclusion: CEUS is more accurate in the diagnosis of renal cystic masses, and it can be used as an effective imaging method.

Background: Currently, there are few literature reports on the CT features of pelvic rhabdomyosarcoma, most of which exist in the form of case reports, and some literature reports have suggested that CT features of pelvic rhabdomyosarcoma lack specificity. This study was designed to investigate the CT features of pelvic RMS in children to provide imaging evidence for clinical diagnosis. Methods: We retrospectively reviewed radiographic and clinical data of all paediatric patients with pelvic neoplastic lesions pathologically proven to be malignant in our hospitals from January 2012 through March 2021. The data of the included paediatric patients were divided into two groups according to whether the pathology results indicated RMS. CT features of RMS (n = 37) and non- RMS (n = 91) were compared by two abdominal radiologists. Results: A total of 9 CT features were statistically significant for the diagnosis of pelvic RMS in children (p < 0.05). The sensitivity (range, 0.64-0.74) and specificity (range, 0.86-0.93) of the CT features showing multinodular fusion, surrounding blood vessels, and heterogeneous progressive centripetal enhancement were both relatively high. The CT features indicating lower than muscle density, necrosis, non-calcification and non-haemorrhage exhibited high specificity (range, 0.86-0.97), but the sensitivity (range, 0.32-0.40) was relatively low, while the sensitivity (range, 0.37-0.46) and specificity (range, 0.75-0.83) of other CT features used for diagnosing pelvic RMS, namely, lobulated and lymphatic metastasis, were both relatively low. Conclusion: Pelvic rhabdomyosarcoma in children has its own specific CT features.

Aims: To investigate the diagnostic value of Dual-energy Computed Tomography (DECT) in Acute Gouty Arthritis (AGA) or patients presenting suspected gouty arthritis. Methods: This retrospective study was performed in a single centre from May 2017 to August 2018. Two hundred and twenty-six patients with an initial diagnosis of AGA in the preceding 15 days were included. All patients were referred for a DECT scan of the affected joints. The diagnosis criteria of gout with the American College of Rheumatology Classification Standard were regarded as the reference standard. Results: After filtration, two hundred patients were included in the present study. The sensitivity, specificity, positive predictive value, and negative predictive value of DECT in the diagnosis of all AGA were 83.83%, 60.61%, 91.5%, and 42.55%, respectively. When AGA was subdivided according to the joint site, the sensitivity, specificity, positive predictive value, and negative predictive value were 80.68%, 61.11%, 91.03%, and 39.29% in feet, 93.55%, 40%, 93.55%, and 40% in knees and 87.5%, 71.43%, 91.3%, and 62.5% in ankles, respectively. Conclusion: DECT had a high sensitivity for the diagnosis of AGA. However, the specificity was limited, particularly for the diagnosis of acute gouty knee arthritis. Prospective multicenter studies of large samples will enhance the application of DECT among AGA patients in the future.

Background: Ground-glass Opacity (GGO) and Consolidation Opacity (CLO) are the common CT lung opacities, and their heterogeneity may have potential for prognosis ofcoronavirus disease-19 (COVID-19) patients. Objective: This study aimed to estimate clinical outcomes in individual COVID-19 patients using histogram heterogeneity analysis based on CT opacities. Methods: 71 COVID-19 cases’ medical records were retrospectively reviewed from a designated hospital in Wuhan, China, from January 24^th to February 28^th at the early stage of the pandemic. Two characteristic lung abnormity opacities, GGO and CLO, were drawn on CT images to identify the heterogeneity using quantitative histogram analysis. The parameters (mean, mode, kurtosis, and skewness) were derived from histograms to evaluate the accuracy of clinical classification and outcome prediction. Nomograms were built to predict the risk of death and median length of hospital stays (LOS), respectively. Results: A total of 57 COVID-19 cases were eligible for the study cohort after excluding 14 cases. The highest lung abnormalities were GGO mixed with CLO in both the survival populations (26 in 42, 61.9%) and died population (10 in 15, 66.7%). The best performance heterogeneity parameters to discriminate severe type from mild/moderate counterparts were as follows: GGO_skewness: specificity= 66.67%, sensitivity=78.12%, AUC=0.706; CLO_mean: specificity=70.00%, sensitivity= 76.92%, and AUC=0.746. Nomogram based on histogram parameters can predict the individual risk of death and the prolonged median LOS of COVID-19 patients. C-indexes were 0.763 and 0.888 for risk of death and prolonged median LOS, respectively. Conclusion: Histogram analysis method based on GGO and CLO has the ability for individual risk prediction in COVID-19 patients.

Background: The clinical and imaging features of lower tibial shaft spiral fracture concurrent with distal tibial triplane fracture are not clear. Introduction: This study was conducted to investigate these features for correct diagnosis, treatment and prevention of possible premature physeal arrest or angular deformation. Methods: Patients with lower tibial shaft spiral fracture concurrent with distal tibial triplane fracture were enrolled, and the clinical, imaging, treatment and follow-up data were analyzed. Results: Five patients with lower tibial shaft spiral fracture concurrent with distal tibial triplane fracture were found including four men and one woman with an age range of 12-15 years (mean 13.6). Injury to the distal tibial epiphysis was missed in the diagnosis in plain radiography reports, but careful reevaluation confirmed distal tibial epiphysis fracture in four cases including Salter-Harris type II in three cases and type III in one case. The remaining case had no apparent distal tibial epiphysis injury in the plain radiograph. CT scan revealed that all five patients had distal tibial triplane fracture of the lateral type including two fragments in three cases and three fragments in two cases. The fracture was divided into type I(within the articular weight-bearing line) in three cases, type II (outside the articular weight-bearing line) in two cases based on the involvement of the articular surface by the fracture line. For the lower tibial fracture, one patient was treated with closed reduction and fixation with an elastic nail, three patients had internal plate fixation, and the remaining patient had cast immobilization. Followed up for 3-11 months (mean 7), all the distal tibial fractures and the triplane fractures were healed without varus or valgus deformity in the ankle. Conclusion: Distal tibial triplane fracture can be readily missed in plain radiography and should be suspected in patients with distal tibial spiral fracture which should be evaluated with a computed tomographic scan.

Background: Artificial Intelligence (AI)-based automatic lung nodule detection system improves the detection rate of nodules. It is important to evaluate the clinical value of the AI system by comparing AI-assisted nodule detection with actual radiology reports. Objective: To compare the detection rate of lung nodules between the actual radiology reports and AI-assisted reading in lung cancer CT screening. Methods: Participants in chest CT screening from November to December 2019 were retrospectively included. In the real-world radiologist observation, 14 residents and 15 radiologists participated in finalizing radiology reports. In AI-assisted reading, one resident and one radiologist reevaluated all subjects with the assistance of an AI system to locate and measure the detected lung nodules. A reading panel determined the type and number of detected lung nodules between these two methods. Results: In 860 participants (57±7 years), the reading panel confirmed 250 patients with >1 solid nodule, while radiologists observed 131, lower than 247 by AI-assisted reading (p<0.001). The panel confirmed 111 patients with >1 non-solid nodule, whereas radiologist observation identified 28, lower than 110 by AI-assisted reading (p<0.001). The accuracy and sensitivity of radiologist observation for solid nodules were 86.2% and 52.4%, lower than 99.1% and 98.8% by AI-assisted reading, respectively. These metrics were 90.4% and 25.2% for non-solid nodules, lower than 98.8% and 99.1% by AI-assisted reading, respectively. Conclusion: Comparing with the actual radiology reports, AI-assisted reading greatly improves the accuracy and sensitivity of nodule detection in chest CT, which benefits lung nodule detection, especially for non-solid nodules.

Background: Manual segment target volumes were time-consuming and inter-observer variability couldn’t be avoided. With the development of computer science, auto-segmentation had the potential to solve this problem. Objective: To evaluate the accuracy and stability of Atlas-based and deep-learning-based auto-segmentation of the intermediate risk clinical target volume, composed of CTV2 and CTVnd, for nasopharyngeal carcinoma quantitatively. Methods and Materials: A cascade-deep-residual neural network was constructed to automatically segment CTV2 and CTVnd by deep learning method. Meanwhile, a commercially available software was used to automatically segment the same regions by Atlas-based method. The datasets included contrast computed tomography scans from 102 patients. For each patient, the two regions were manually delineated by one experienced physician. The similarity between the two auto-segmentation methods was quantitatively evaluated by Dice similarity coefficient, the 95th Hausdorff distance, volume overlap error and relative volume difference, respectively. Statistical analyses were performed using the ranked Wilcoxon test. Results: The average Dice similarity coefficient (±standard deviation) given by the deep-learning- based and Atlas-based auto-segmentation were 0.84 (±0.03) and 0.74 (±0.04) for CTV2, 0.79 (±0.02) and 0.68 (±0.03) for CTVnd, respectively. For the 95^th Hausdorff distance, the corresponding values were 6.30±3.55 mm and 9.34±3.39 mm for CTV2, 7.09±2.27 mm and 14.33±3.98 mm for CTVnd. Besides, volume overlap error and relative volume difference could also predict the same situations. Statistical analyses showed significant difference between the two auto-segmentation methods (p<0.01). Conclusion: Compared with the Atlas-based segmentation approach, the deep-learning-based segmentation method performed better both in accuracy and stability for meaningful anatomical areas other than organs at risk.

Background: Diverticula are commonly observed in the duodenum. Duodenal Diverticulum (DD) usually does not give symptoms throughout life and is diagnosed by coincidence. However, it may present with different symptoms in patients. Objective: This study aims to evaluate the prevalence of DD and Juxtapapillary Duodenal Diverticulum (JDD) and its association with other possible pathologies and to determine its clinical impact by using Computed Tomography (CT). Methods: This retrospective observational study, which was taken consecutively between the years of 2013-2020, was evaluated in the Radiology Department. The total number of cases was 4850 (male-2440; female-2410). CT images were evaluated by two experienced radiologists at the workstation. DD and JDD prevalence and clinical findings in the hospital registry system were examined. Results: The age of the patients included in the study ranged from 17 to 92 years (mean age 46.94±16.42). In patients with DD (female-130; male-101), mean age was 62.24 ± 12.69 (21-92). The prevalence of DD was 4.76% (n=231). The prevalence of JDD was 4.02% (n=195) and increased with age (p<0.01). The average diameter of the JDD was measured as 23.29±8.22 (9.5-55.3) mm. A significant positive correlation was found between age and DD diameter (p=0.039). DDs were found most commonly 84.42% (n=195) in the second segment of the duodenum as JDD. In patients with JDD, the mean diameter of choledochus and wirsung canal were 6.7 ± 2.4 (3-15.3) mm and 0.31 ± 0.1 (0.1-6.5) mm respectively. The choledochal diameter was correlated with the JDD size (p = 0.004). Cholelithiasis (n=56), choledocholithiasis (n=20), cholecystitis (n=52), diverticulitis (n=15), duodenitis (n=37), pancreatitis (n=5) and hiatal hernia (n=60) with JDD were observed. Periampullary carcinoma was detected in one patient. Conclusion: Our study shows that cholelithiasis, choledocholithiasis, cholecystitis, diverticulitis, duodenitis, pancreatitis may be associated with JDD. Therefore, in contrast-enhanced abdominal CT scans taken for various reasons, investigation of the presence and characteristics of JDD and detection of pathologies that may be associated with JDD are important for patients to benefit from early diagnosis and treatment opportunities and to take precautions against possible complications.

Background: Benign external compression of the Inferior Vena Cava (IVC) with distal thrombus formation is seldomly described in the medical literature. Case Presentations: We report a case of external IVC compression by a dilated right renal pelvis and hydronephrotic kidney secondary to longstanding Ureteropelvic Junction (UPJ) obstruction found in a 68-year-old male. Management included therapeutic anticoagulation, IVC filter placement, attempted thrombectomy by interventional radiology, and interval repeats imaging. This patient demonstrated complete resolution of the caval thrombus on repeat imaging 2 months following discharge. This case highlights the importance of interdisciplinary team coordination, a crucial component of patient’s management and eventual treatment plan. It is reasonable to manage patients with IVC thrombus with anticoagulation alone. Conclusion: In the modern era, angiointerventional techniques provide minimally invasive approaches to the management of vascular disorders and minimize morbidity.

Background: Pseudolymphoma of the liver (Reactive Lymphoid Hyperplasia) (RLH) is a rare condition. It is usually asymptomatic and detected incidentally on radiological imaging. Imaging features are similar to hepatic adenoma, hepatocellular carcinoma, cholangiocarcinoma, and malignant lymphoma and are not specific for pseudolymphoma of the liver. Percutaneous core biopsy is insufficient to distinguish pseudolymphoma of the liver from low-grade malignant lymphoma and extranodal marginal lymphomas. Case Descriptions: In this article, we present a case of hepatic RLH of a patient who was presented with a skin rash on the leg and was detected incidentally on radiological imaging. Conclusion: Preoperative definitive diagnosis of hepatic RLH using various imaging methods, including MRI with hepatocellular agents, is highly difficult.

We apologize for the error that occurred in the online version of the article. Table 3 was missing in the article entitled “Application of Two New Feature Fusion Networks to Improve Real-time Prostate Capsula Detection” in “Current Medical Imaging”, 2021; 17(9): 1128-36 [1]. The original article can be found online at https://www.eurekaselect.com/article/113786 Original: Table 3 was missing. Corrected: Table 3 has been added.