Current Medical Imaging Reviews最新文献

Introduction: Struma ovarii (SO) is a rare ovarian teratoma composed predominantly of thyroid tissue, often misdiagnosed due to its non-specific clinical manifestations and low prevalence.

Methods: The ultrasound and clinical features of 16 histologically confirmed cases of SO (mean age 45 ± 10 years) were analyzed. Key ultrasound parameters evaluated included tumor size, internal echo patterns, calcification, blood flow (Adler grading), and pelvic effusion.

Results: Half of patients with SO have been found to be postmenopausal women over 50 years of age, and that most tumors are discovered incidentally during routine examination. The large cystic components with regular margins, accompanied by calcified and vascularized solid elements, are ultrasound characteristics of SO. In particular, the presence of calcification and distinct vascular patterns on Doppler imaging (as per Adler classification) has been identified as a critical marker distinguishing SO from other adnexal masses.

Discussion: Compared to existing SO research, this study has found the ultrasound characteristics of SO to mostly manifest as a large cystic echo, regular boundaries, and calcification. At the same time, compared to the existing imaging techniques, such as CT and MRI, characteristic ultrasonography has been found to be a good complement to the diagnosis of SO.

Conclusion: When an adnexal tumor is classified as O-RADS 3-5 and exhibits features, such as a large cystic echo, regular boundaries, and calcification, SO should be considered in the differential diagnosis. These findings can enhance the accuracy of preoperative assessment, facilitate individualized surgical planning, and contribute to improved clinical management by reducing the likelihood of misdiagnosis.

Introduction: This case highlights the rare but life-threatening complication of carotid blowout syndrome (CBS) after radiotherapy for nasopharyngeal carcinoma (NPC). It is characterized by rupture of the carotid artery, often occurring months or years after treatment. Early diagnosis and timely intervention are essential to improve clinical outcomes.

Case presentation: A 45-year-old woman with NPC developed recurrent epistaxis 31 months after chemoradiotherapy. MRI and MRA ruled out tumor recurrence. High-resolution vessel wall imaging (VWI) revealed eccentric thickening, irregular enhancement, and a pseudoaneurysm in the lacerum segment of the left internal carotid artery (ICA), which was confirmed by CTA and DSA. The patient underwent embolization and remained stable at 1-year follow-up.

Conclusion: This case underscores the value of VWI in detecting CBS-related vascular changes. Imaging is crucial for early diagnosis and timely intervention in high-risk patients with NPC who have undergone radiotherapy.

Introduction/background: Cytotoxic lesions of the corpus callosum (CLOCC) are a rare clinical-radiological syndrome, and cases occurring consecutively in siblings are exceptionally uncommon. This study reports two pediatric siblings with CLOCC (one experiencing two episodes), highlighting the potential role of genetic susceptibility in its pathogenesis. The findings contribute to the limited literature on familial CLOCC and recurrent cases, offering insights into its etiology and clinical variability.

Case presentation: Two brothers (aged 9 and 12) presented with sudden-onset aphasia and unilateral limb weakness, preceded by mild respiratory symptoms. Magnetic resonance imaging (MRI) revealed reversible lesions in the splenium of the corpus callosum and bilateral frontoparietal white matter, consistent with CLOCC. Both patients received immunomodulatory therapy (e.g., corticosteroids, intravenous immunoglobulin) and supportive care, achieving full neurological recovery within days. The elder sibling had a recurrence two years later with similar imaging findings. Laboratory tests ruled out common infections, and cerebrospinal fluid analysis was unremarkable.

Conclusion: This case underscores CLOCC as a heterogeneous condition with possible genetic predisposition, as evidenced by its occurrence in siblings. While prognosis is generally favorable, recurrence and familial clustering suggest the need for further research into underlying genetic or immunological mechanisms. Clinicians should consider CLOCC in children with acute neurological deficits and prior infections, even in the absence of typical biomarkers.

Introduction: This study aimed to evaluate the impact of orthodontic extraction treatment on mandibular third molar impaction by measuring changes in angulation before and after treatment in patients receiving extraction versus non-extraction orthodontic therapy.

Methods: A retrospective analysis was conducted on 30 patients who completed fixed orthodontic treatment at the Department of Stomatology, Deyang People's Hospital, between 2018 and 2023. Patients were divided into two groups, with 15 included in the extraction group and 15 in the nonextraction group. Pre- and post-treatment orthopantomograms (OPGs) were analyzed, with each mandibular third molar quadrant considered an independent sample. Changes in the α-angle of mandibular third molars were compared between the groups.

Results: The mean change in α-angle was -2.42° ± 8.32° in the non-extraction group and 4.85° ± 9.53° in the extraction group, with a statistically significant difference between the two groups (p < 0.05).

Discussion: Whether orthodontic extraction treatment facilitates third molar eruption remains a topic of ongoing debate. Differences in conclusions across studies may be attributed to variations in sample selection, patient age, growth stage, anchorage strategies, and imaging methodology. Our study design attempted to control for these variables by matching participants by age, sex, and treatment duration, and by ensuring comparable baseline α-angle in both groups to minimize confounding. Further prospective studies based on three-dimensional imaging are still needed in the future to validate our conclusions.

Conclusion: Orthodontic treatment involving premolar extraction significantly improved the angulation of mandibular third molars compared to non-extraction treatment, potentially reducing impaction severity and enhancing eruption potential.

Purposes: Deep learning methods were employed to perform harmonization analysis on whole-brain scans obtained from 1.5-T and 3.0-T scanners, aiming to increase comparability between different magnetic resonance imaging (MRI) scanners.

Methods: Thirty patients evaluated in Beijing Tsinghua Changgung Hospital between August 2020 and March 2023 were included in this retrospective study. Three MRI scanners were used to scan patients, and automated brain image segmentation was performed to obtain volumes of different brain regions. Differences in regional volumes across scanners were analyzed using repeated-measures analysis of variance. For regions showing significant differences, super-resolution deep learning was applied to enhance consistency, with subsequent comparison of results. For regions still exhibiting differences, the Intraclass Correlation Coefficient (ICC) was calculated and the consistency was evaluated using Cicchetti's criteria.

Results: Average whole-brain volumes for different scanners among patients were 1152.36mm³ (SD = 95.34), 1136.92mm³ (SD = 108.21), and 1184.00mm³ (SD = 102.78), respectively. Analysis revealed significant variations in all 12 brain regions (p<0.05), indicating a lack of comparability among imaging results obtained from different magnetic field strengths. After deep learning-based consistency optimization, most brain regions showed no significant differences, except for six regions where differences remained significant. Among these, three regions demonstrated ICC values of 0.868 (95%CI 0.771-0.931), 0.776 (95%CI 0.634-0.877), and 0.893 (95%CI 0.790-0.947), indicating high reproducibility and comparability.

Conclusion: This study employed a novel machine learning approach that significantly improved the comparability of imaging results from patients using different magnetic field strengths and various models of MRI scanners. Furthermore, it enhanced the consistency of central nervous system image segmentation.

Objective: To evaluate the correlation between the effective cross-sectional area (eCSA) of the Rotator Cuff muscle measured using Dixon MRI and the outcomes of the Biodex Isokinetic Test.

Methods: The cross-sectional area (CSA) of the subscapularis (SSc), supraspinatus (SST), and infraspinatus+teres minor (ISTM) muscles of 87 patients who had undergone shoulder MRI and Biodex Isokinetic Test were measured in the oblique sagittal Y-view. The eCSA was calculated by multiplying the CSA by (1-fat fraction). Eight shoulder movements (FL60, EX60, FL180, EX180, ER60, IR60, ER180, and IR180) with four parameters (peak torque [PT], peak torque/body weight, torque at 30° [TQ30], and total work) were recorded on Biodex. Pearson correlation coefficients were calculated between eCSA and Biodex outcomes. Univariate regression analyses were conducted to identify the factors influencing the Biodex results. General linear models were applied to confirm the correlations between the eCSA and 32 Biodex parameters after adjusting for these factors.

Results: The eCSA of the SSc, SST, and ISTM exhibited significant correlations with TQ30 at IR180 (r=0.549) and FL60 (r=0.522), PT at ER60 (r=0.656) and EX60 (r=0.575), and PT at ER60 (r=0.674) and FL180 (r=0.626), respectively. Age, sex, SST, and SSc tears were identified as factors influencing the Biodex results. FL60TQ30, ER60PT, and EX60PT exhibited significant associations with the eCSA of SSc, SST, and ISTM, respectively, after adjusting for these factors.

Conclusion: eCSA may be a useful quantitative imaging marker for assessing the function of the Rotator Cuff muscle. FL60TQ30, ER60PT, and EX60PT are useful Biodex indices for SSc, SST, and ISTM, respectively.

Purpose: The pool sign, an emerging MRI biomarker for differentiating brain metastases (BM) from primary neoplasms, is primarily documented in case reports. Systematic data on its prevalence and determinants in BM among patients with lung cancer are lacking. This study aims to evaluate the occurrence of the pool sign and identify factors associated with its presence.

Materials and methods: Between January 2017 and August 2024, data from 6,004 lung cancer patients were retrospectively extracted from the electronic health records system. The clinical and demographic characteristics, along with BM MRI features, were compared between the pool sign and non-pool sign groups using univariate and multivariate analyses.

Results: A total of 427 patients (81 women; mean age, 62.17 years) were enrolled in the study. The pool sign was observed in 29 patients (6.8%). The interreader reliability for the pool sign ranged from moderate to substantial (κ=0.61-0.80), while the intra-reader reliability was moderate (κ=0.6). In the univariate analysis, a statistically significant difference was observed in the volume size of metastases between the pool sign group and the non-pool sign group (median 4.8 vs. 0.5, P < 0.0001). This finding suggests that the presence of the pool sign is more likely associated with BMs exhibiting relatively larger tumor volumes. Additionally, the prevalence of solid-cystic masses was significantly higher in the pool sign group compared to the non-pool sign group, with rates of 79.3% and 44.5%, respectively (P = 0.0014). However, there were no statistically significant differences in other examined variables. In the multivariate analysis, the findings demonstrated that an increase in tumor volume (OR = 1.050, 95% CI 1.025-1.076, P < 0.001) and the presence of a solid-cystic mass (OR = 3.666, 95% CI 1.159-11.595, P = 0.027) were significantly correlated with a higher probability of pool sign occurrence.

Conclusion: The pool sign occurs in 6.8% of BM in patients with lung cancer and is independently associated with larger lesion volume and solid-cystic morphology. Its diagnostic utility warrants further validation.

Introduction: Prenatal intervention with fetoscopic endoluminal tracheal occlusion (FETO) using a balloon can stimulate lung growth and improve neonatal survival for moderate and severe congenital diaphragmatic hernia (CDH). Quantitative parameters measured on magnetic resonance imaging (MRI) can guide the treatment of CDH and evaluate changes after FETO treatment.

Case presentation: We reported on five cases of isolated left congenital diaphragmatic hernia (CDH) in fetuses who underwent FETO surgery. We conducted a comparison of the MRI images before and after FETO treatment and analyzed the correlation between the observed changes and the clinical outcomes of the neonates after delivery.

Conclusion: MRI can precisely provide the anatomical details of CDH and quantitatively analyze changes in fetal lung volume before and after FETO surgery.

Introduction: Artificial intelligence has significantly enhanced disease diagnosis in healthcare, particularly through Deep Learning (DL) and Federated Learning (FL) approaches. These technologies have shown promise in detecting ocular diseases using medical imaging while addressing challenges related to data privacy and security. FL enables collaborative learning without sharing sensitive medical data, making it an attractive solution for healthcare applications. This systematic review aims to analyze the advancements in AI-driven ocular disease detection, with a particular focus on FL-based approaches. The article evaluates the evolution, methodologies, challenges, and effectiveness of FL in enhancing diagnostic accuracy while ensuring data confidentiality.

Methods: The systematic review followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework to ensure transparency and reliability. Research articles published between 2017 and 2024 were identified using academic databases, including Web of Science, Scopus, IEEE Xplore, and PubMed. Studies focusing on DL and FL models for detecting ocular diseases were selected based on predefined inclusion and exclusion criteria. A comparative analysis of the methodologies, architectures, datasets, and performance metrics of different FL models has been presented.

Results and discussion: The findings indicated that FL preserves data privacy while achieving diagnostic performance comparable to traditional centralized AI models. Various FL models, including FedAvg and FedProx, have been implemented for ocular disease detection, with high accuracy and efficiency. However, challenges, such as data heterogeneity, communication efficiency, and model convergence, persist.

Conclusion: FL represents a promising approach for ocular disease detection, balancing diagnostic accuracy with data privacy. Future research may focus on optimizing FL frameworks for improving scalability, communication efficiency, and integrating advanced privacy-preserving techniques.

Introduction: Early detection of gastric cancer remains challenging for many of the current imaging techniques. Recent advancements in reduced field-of-view (rFOV) diffusion-weighted imaging (DWI) have shown promise in improving the visualization of small anatomical structures. This study aimed to evaluate and compare the diagnostic performance of rFOV DWI with multi-detector computed tomography (MDCT) and conventional full field of view (fFOV) DWI for detecting early gastric cancer (EGC).

Methods: This retrospective study included 43 patients with pathologically confirmed EGC. All participants underwent pre-treatment imaging, including CT scans and MRI with a prototype rFOV DWI and conventional fFOV DWI at 3 Tesla. Quantitative (signal-to-noise ratio [SNR], contrast-to-noise ratio [CNR]) and qualitative (subjective image quality) assessments were performed. Diagnostic performance was evaluated using receiver operating characteristic (ROC) curves and area-under-the-curve (AUC) analysis.

Results: rFOV DWI demonstrated significantly higher SNR and CNR compared with fFOV DWI (P < 0.05). Subjective image quality scores were also superior for rFOV DWI (P < 0.05). In lesion detection, rFOV DWI showed higher sensitivity (0.705) than CT (0.636) and fFOV DWI (0.523). ROC analysis revealed that rFOV DWI had a higher AUC (0.829, 95% CI [0.764, 0.882]) than fFOV DWI (0.734, 95% CI [0.661, 0.798], P = 0.02) and a modest improvement over CT (0.799, 95% CI [0.731, 0.856], P = 0.51).

Discussion: The findings suggest that rFOV DWI provides superior image quality and diagnostic accuracy for EGC detection compared with conventional fFOV DWI. While it showed a trend toward better performance than CT, further studies with larger cohorts are needed to validate these results.

Conclusion: rFOV DWI offers improved image quality and diagnostic performance for early gastric cancer detection compared with fFOV DWI, with a potential advantage over CT. This technique may enhance early diagnosis and clinical decision-making in gastric cancer management.