Current Medical Imaging Reviews最新文献

Purpose: This study aimed to evaluate the Pharmacovigilance (PV) and severity of hypersensitivity reactions induced by non-ionic Iodinated Contrast Media (ICM) in the radiology diagnosis reported to the United States Food and Drug Administration Adverse Event Reporting System (FAERS).

Methods: We retrospectively reviewed the reports of ICM-induced hypersensitivity reactions submitted to the FAERS database between January 2015 and January 2023 and conducted a disproportionality analysis. The seven most common non-ionic ICM, including iohexol, iopamidol, ioversol, iopromide, iomeprol, iobitridol, and iodixanol, were chiefly analyzed. Our primary endpoint was the PV of non-ionic ICM-induced total hypersensitivity events. STATA 17.0 MP was used for statistical analysis.

Results: In total, 35357 reports of adverse reaction events in radiology diagnosis were retrieved from the FAERS database. Among them, 6181 reports were on hypersensitivity reaction events (mean age: 57.1 ± 17.8 years). The hypersensitivity reaction-related PV signal was detected for iohexol, ioversol, iopromide, iomeprol, iobitridol, and iodixanol, but not for iopamidol. The proportion of iomeprol-induced hypersensitivity reactions and the probability of ioversol-induced severe hypersensitivity reactions have been found to be significantly increased.

Conclusion: The probability and severity of hypersensitivity reaction events in non-ionic ICM are different. Iohexol, ioversol, iopromide, iomeprol, iobitridol, and iodixanol have higher risks compared to iopamidol. In addition, the constituent ratio of hypersensitivity reactions induced by iomeprol is significantly increased, and the associated probability induced by ioversol is significantly increased.

Background: The neural mechanisms underlying congenital sensorineural hearing loss (CSNHL) remain elusive.

Objective: This study evaluated the function of the glymphatic system in children with CSNHL compared to normal-hearing children using the DTI-ALPS approach, which utilizes diffusion tensor imaging along the perivascular space.

Methods: Twenty-six children with CSNHL and 30 age- and sex-matched healthy controls (HCs) with normal hearing thresholds were recruited. The DTIALPS index was calculated for each group. We analyzed the discrepancies in the DTI-ALPS index between patients with CSNHL and healthy controls. Additionally, Spearman's correlation analysis was performed to investigate the relationship between the DTI-ALPS index and age in children with CSNHL.

Results: Significant differences in the DTI-ALPS index were observed between the two groups. Compared with HCs, the DTI-ALPS index in CSNHL patients was significantly lower (1.49388±0.11441 vs. 1.61402±0.15430, p=0.002). In addition, diffusivity along the z-axis in the association fiber (Dzzassoc) index was significantly higher in the CSNHL group than in the HC group (0.00041±0.00006 vs. 0.00036±0.00004, p=0.003). Furthermore, we discovered a noteworthy downward correlation between the DTI-ALPS index and age in children with CSNHL (rho = -0.544, p=0.005).

Conclusion: In this present study, glymphatic system activity in CSNHL children was investigated for the first time using the DTI-ALPS index. A significant decrease in glymphatic system function was detected in CSNHL children, which correlated well with age. The DTI-ALPS index could serve as a valuable biomarker for tracking disease progression and treatment in CSNHL and unraveling the neural mechanisms of early hearing deprivation in children with CSNHL.

Background: Chronic Kidney Disease [CKD] affects individuals of different age groups worldwide. Moreover, CKD is associated with several risk factors, including obesity, lifestyle, and hypertension, which are common in the Middle East. Ultrasonography is the examination of choice for CKD. In recent years, Shear Wave Elastography [SWE] has developed through the continued development of ultrasound and received substantial attention ;therefore, it can be used to measure tissue stiffness. The study aimed to use point Shear Wave Elastography [p-SWE] to determine the correlation between diabetes and cortical renal thickness in detecting pathologies.

Methods: This study was performed at the King Abdul-Aziz University Hospital. We examined 61 patients who underwent SWE. The patients were classified into two groups based on the presence or absence of type 2 Diabetes Mellitus [DM].

Results: The results showed that there was a significant correlation between cortical stiffness and DM duration [p<0.005]. In addition, there was a negative correlation between cortical stiffness and cortical thickness [p=0.147] in patients with DM. Moreover, the eGFR decreased with an increase in cortical stiffness [p=0.499]. The cortical thickness in patients with and without DM was 0.750 ± 0.2 kPa and 0.788 ± 0.4 kPa, respectively. The kidney stiffness in patients with DM and control patients was 8.5 ± 8.6 cm and 14.0 ± 25.16 cm, respectively.

Conclusion: This study showed that kidney p-SWE measurements were reliable. Therefore, further studies assessing kidney stiffness in patients with and without people with diabetes are recommended.

Introduction: In developing Computer-Aided Diagnosis (CAD), a Convolutional Neural Network (CNN) has been commonly used as a Deep Learning (DL) model. Although it is still early, DL has excellent potential in implementing computers in medical diagnosis.

Methods: This study reviews the use of DL for Anterior Cruciate Ligament (ACL) tear diagnosis. A comprehensive search was performed in PubMed, Embase, and Web of Science databases from 2018 to 2024. The included study criteria used MRI images to evaluate ACL tears, and the diagnosis of ACL tears was performed using the DL model. We summarized the paper by reporting their model accuracy, model comparison with arthroscopy, and explainable.

Results: AI implementation in tabular format; we conclude that many medical professionals believe that arthroscopic diagnosis is the most reliable method for diagnosing ACL tears. However, due to its intrusive treatment, CAD is projected to be able to produce similar outcomes from MRI scan results. To gain the trust of physicians and meet the demand for reliable knee injury detection systems, an algorithm for CAD should also meet several criteria, such as being transparent, interpretable, explainable, and easy to use. Therefore, future works should consider creating an Explainable DL model for ACL tear diagnosis. It is also essential to evaluate the performance of this Explainable DL model compared to the gold standard of arthroscopy diagnosis.

Conclusion: There are issues regarding the need for Explainable DL in CAD to increase confidence in its result while also highlighting the importance of the involvement of medical practitioners in system design. There is no funding for this work.

Purpose: Individuals with depression have an increased risk of cardiovascular disease, and more often have a poor prognosis with cardiovascular disease. This study aimed to investigate the impact of depression on Left Ventricular (LV) alterations using Cardiovascular Magnetic Resonance Featuretracking (CMR-FT).

Methods: Seven anesthetized, healthy Chinese miniature swine were included in the study. Basic data, including CMR scans at baseline and after 14 days of depression modeling, were collected. Behavioral tests, including the Open-field Test (OFT), Sucrose Preference Test (SPT), and measurements of the time taken to consume a specific amount of food and sugar, were conducted to assess the success of the depression models. CMR cine images were acquired and CVI software was employed to analyze Global Longitudinal Strain (GLS), Global Circumferential Strain (GCS), and Global Radial Strain (GRS). Late Gadolinium Enhancement (LGE) imaging was used to detect myocardial infarction and/or scar.

Results: The outcomes demonstrated successful depression modeling, indicated by reduced scores in the OFT and SPT, as well as an extended time to intake food and sugar compared to baseline. However, no significant differences were observed in LV End-diastolic Volume (LVEDV), LV Endsystolic Volume (LVESV), LV Ejection Fraction (LVEF), LV End-diastolic Myocardial Mass (LVMASSED), and Cardiac Output (CO) before and after modeling. Regarding LV global strain parameters, there was a downward trend in GRS (25.35% ± 6.9% vs. 22.86% ± 6.4%, P=0.021), GCS (-16.71% ± 4.2% vs. -14.78% ± 2.3%, P=0.043), and GLS (-17.66% ± 2.9% vs. -14.53% ± 2.5%, P=0.056), respectively, after modeling. GRS and GCS were significantly reduced after modeling compared to baseline.

Conclusion: The study suggests that depression may contribute to early LV systolic dysfunction, particularly affecting LV GCS and GRS.

Background: Applications of artificial intelligence (AI) in medical ultrasound have rapidly grown in recent years. Therefore, it is necessary to identify and visualize global research trends and hotspots of AI in medical ultrasound to provide guidance for further exploitation.

Objective: This study aims to highlight the global research trends and hotspots of the top 100 most-cited papers related to AI in medical ultrasound by combining quantitative and visualization methods.

Methods: Articles on AI in medical ultrasound were selected from the WoSCC database and ranked by citation count. After identifying the 100 most-cited papers, we conducted a quantitative and visualized analysis of bibliometric characteristics, including leading research countries, prominent institutions, key authors and journals, author clusters and collaborations, and keyword co-occurrence network analysis.

Results: The top 100 highly cited papers from the WoSCC database were published between 1999 and 2021, with total citations ranging from 91 to 1580. The most cited article was published in IEEE Transactions on Medical Imaging. The top three most prolific countries/regions were the United States, mainland China, and the United Kingdom. The most published institutions and journals were Idaho University and IEEE Transactions on Medical Imaging. Twelve authors published more than four papers, with Suri, JS being the most productive author. The most studied topics were "ultrasound", "computer-aided diagnosis", and "segmentation". Ultrasonography of Superficial Organs was the main site that was studied the most.

Conclusion: This study provides comprehensive insights into the characteristics of AI in medical ultrasound through quantitative and visualized analysis of the most highly cited literature. It serves as a valuable reference for the development and applications of AI, fostering potential collaborations within this domain.

Purpose: This study aimed to verify whether the Liver-to-portal Ratio (LPR) can assess the adequacy of the Hepatobiliary Phase (HBP) for patients with different liver functions.

Methods: A total of 125 patients were prospectively enrolled in the study and graded into the non-cirrhosis group (45), Child-Pugh A group (40), and Child- Pugh B/C group (40). The LPR on HBP was calculated after eight HBPs were obtained within 5-40 minutes. The adequate HBP was determined according to the 2016 European Society of Gastrointestinal and Abdominal Radiology (ESGAR) consensus statement. The differences in LPR and lesions' conspicuity between 10-min HBP and adequate HBP were analyzed by paired t-test and Wilcoxon signed-rank test, respectively. The chisquare test was used to test the difference in proportion with LPR larger than 1.462 between 10-min HBP and adequate HBP.

Results: The differences in LPR and lesions' conspicuity between 10-min HBP and adequate HBP were significant in Child-Pugh A and Child-Pugh B/C groups (P < 0.05), except for the non-cirrhosis group (P > 0.05). The differences in proportion with LPR larger than 1.462 between 10-min HBP and adequate HBP were not statistically significant in all groups (all P > 0.05).

Conclusion: The adequate HBP obtained according to the 2016 ESGAR consensus statement could provide larger LPR and better lesions' conspicuity than 10- min HBP, especially for cirrhotic patients; however, the efficacy of using an LPR cutoff of 1.462 as the standard of the adequate HBP may be compromised in patients with cirrhosis.

Background: While cerebral cavernous malformations (CCMs) have been extensively described, few reports have described the imaging appearance of giant CCMs (GCCMs).

Objective: To describe the imaging characteristics of GCCMs and study the reasons for preoperative misdiagnosis.

Methods: We retrospectively analyzed the data of 12 patients (5 men, 7 women; mean age, 35.23 ± 12.64 years) with histopathologically confirmed GCCMs. Two radiologists analyzed the CT (n = 12) and MRI (n = 10) features: location, number, size, shape, boundary, signal intensity, and enhancement.

Results: The sellar region, cerebral hemisphere, skull bone, and ventricle were involved in 5, 4, 2, and 1 patients, respectively. Three tumors were irregularly shaped, while nine were oval. Eleven lesions showed slightly high- and/or high-density on CT; 1 lesion appeared as a low-density cyst. Calcifications were found in 11 lesions. Four tumors showed uniform hypointensity on T1-weighted imaging (T1WI) and hyperintense signals on T2-weighted imaging (T2WI). Six tumors showed mixed low-, equal-, and high-intensity signals on T1WI and T2WI. Noticeable contrast enhancement and gradual strengthening were noted on T1WI. Ten lesions showed hemorrhage and hemosiderin deposition. The GCCMs were wrongly diagnosed as cartilage-derived tumors/ meningioma (3 patients); tumor and hematoma (2 patients each); and pituitary tumor/ meningioma, chondroma, chordoma, ependymoma, and macroadenoma (1 patient each).

Conclusions: GCCMs present as an oval mass with slightly high- and/or high-density calcifications on CT and show hemorrhage and hemosiderin accumulation on MRI. Therefore, slightly high- and/or high-density calcification and hemosiderin accumulation are critical clinical characteristics of GCCMs.

Objective: The purpose of this study was to assess the diagnostic value of magnetic resonance imaging (MRI) in staging and treatment of cervical cancer in pregnancy, and to evaluate the benefit of apparent diffusion coefficient (ADC) during neoadjuvant chemotherapy management.

Materials and methods: This was a retrospective cohort study. Patients were divided into two groups according to the stage of cervical cancer. The mean term of pregnancy at the time of the diagnosis was the early second trimester (range 10-27 weeks) and the median age was 33 years (range 26-40 years). The abdominal and pelvic MRI images and clinical data of these patients were reviewed. Tumor size, local tumor spread, and nodal involvement were evaluated using an MRI dataset. The treatment and follow-up imaging were analyzed as well, and the ADC was measured before and after the chemotherapy.

Results: 16 patients with histopathologically confirmed cervical cancer during pregnancy were retrospectively enrolled. 7 patients were diagnosed with local cervical cancer (FIGO stage IAI) and designated as early stage group, as the lesion was invisible on MRI. In this group, pregnancies were allowed to continue until cesarean delivery (CD) at 38-41 weeks. The other 9 patients presenting with local or extensive cervical cancer (FIGO stage IB2-IIA2) were designated as the advanced-stage group. The lesion could be measured and analyzed on MRI. They were treated with neoadjuvant chemotherapy in pregnancy. Among them, 6 patients underwent TP regimen (paclitaxel 135~175 mg/m2 plus cisplatin 70~75 mg/m2), while 3 patients received TC regimen (paclitaxel 135~175 mg/m2 plus carboplatin AUC=5). NACT was performed for 1 to 2 courses before surgery. ADC demonstrated significant differences before and after chemotherapy administered during pregnancy (1.06 ± 0.12 sec/mm2 vs. 1.34 ± 0.21 sec/mm2).

Conclusion: MRI has been found to be helpful in staging cervical cancer in pregnancy. Patients with stage IA confirmed by MRI can choose conservative treatment and continue the pregnancy until term birth. MRI can dynamically monitor the efficacy of chemotherapy for patients with stage IB and above during pregnancy. ADC value can have a potential role in the evaluation of chemotherapy efficacy.

Background: Accurately predicting the hepatocellular carcinoma (HCC) grade may facilitate the rational selection of treatment strategies. The diagnostic efficacy of the combination of Gadolinium ethoxybenzy diethylenetriamine pentaacetic (Gd-EOB-DTPA) enhancement T1 mapping and apparent diffusion coefficient (ADC) values in predicting HCC grade needs further validation.

Objectives: This study aimed to assess the capacity of Gd-EOB-DTPA-enhanced T1 mapping and ADC values, both individually and in combination, to discriminate between different grades of HCC.

Materials and methods: From July 2017 to February 2020, 96 patients (male, 83; mean age, 53.67 years; age range, 29-71 years) clinically diagnosed with HCC were included in the present study. All patients underwent Gd-EOB-DTPA-enhanced magnetic resonance imaging (MRI, including T1 mapping sequence) before surgery or biopsy. All the patients were categorized into 3 groups according to the pathological results (including 24 cases of well-differentiated HCCs, 59 cases of moderately differentiated HCCs, 13 cases of and poorly differentiated HCCs). The mean Gd-EOB-DTPA enhanced T1 values (ΔT1=[(T1pre-T1post)/T1pre]×100%) and ADC values between different grading groups of HCC were calculated and compared. The area under the characteristics curve (AUC), the diagnostic threshold, sensitivity, and specificity of ΔT1 and ADC for differential diagnosis were analyzed.

Results: Mean ΔT1 was 58% for well-differentiated HCCs, 50% for moderately-differentiated HCCs, and 43% for poorly-differentiated HCCs. ΔT1 showed statistical differences between the groups (P<0.001). The mean ADC values of the 3 groups were 1.11×10-3 mm2/s, 0.91×10-3 mm2/s, and 0.80×10-3mm2/s, respectively. ADC showed statistical differences between the groups (P<0.001). In discriminating well- differentiated group from the moderately differentiated group, the AUC of ΔT1 was 0.751 (95% CI: 0.642, 0.859), the AUC of ADC was 0.782 (95% CI: 0.671, 0.894), the AUC of combined model was 0.811 (95% CI: 0.709, 0.914). In discriminating the poorly differentiated group from the moderately differentiated group, the AUC of ΔT1 was 0.768 (95% CI: 0.634, 0.902), the AUC of ADC was 0.754 (95% CI: 0.603, 0.904), and the AUC of the combined model was 0.841 (95% CI: 0.729, 0.953).

Conclusion: Gd-EOB-DTPA enhanced T1 mapping, and ADC values have complementary effects on the sensitivity and specificity for identifying different HCC grades. A combined model of Gd-EOB-DTPA-enhanced MRI T1 mapping and ADC values could improve diagnostic performance for predicting HCC grades.