Current Medical Imaging - Current Issue

The Myocardial Salvage Index (MSI) is a valuable indicator in ST-segment Elevation Myocardial Infarction (STEMI) treated with Percutaneous Coronary Intervention (PCI), yet challenges exist in its acquisition. This study aims to calculate MSI using Coronary Angiography (CAG) and myocardial perfusion imaging, and further investigate its correlation with long-term cardiac function.

In 203 STEMI, the myocardium at risk was measured through CAG using the Bypass Angioplasty Revascularization Investigation Myocardial Jeopardy Index (BARI) score. The infarcted myocardium was measured by the Total Perfusion Deficit (TPD) obtained in Myocardial Perfusion Imaging (MPI) after PCI. MSI was computed as (BARI score–TPD)/BARI score. Long-term cardiac function was assessed via echocardiography.

The MSI is notably associated with the long-term cardiac function [EF: Beta = 16 (13, 20), P < 0.00; LVD: Beta = -7.3 (-9.3, -5.3), P < 0.001]. TIMI flow grades 2-3 demonstrate a superior MSI compared to grades 0-1 [0.78 (0.32) vs. 0.61 (0.38), P = 0.002]. TIMI flow grades have an impact on MSI [Beta = 0.08 (0.04, 0.13), P < 0.001]. Compared to patients with a Killip grade of < 2, those with a grade ≥ 2 exhibit a lower MSI [0.69 (0.35) vs. 0.48 (0.42), p = 0.005]. The Killip classification has an impact on MSI [Beta = -0.12(-0.19, -0.04), P = 0.003].

The study indicates the pivotal role of MSI in predicting long-term cardiac function in STEMI, compares the advantages and limitations of SPECT, CMR, and hybrid SPECT/CAG methods, analyzes the impact of residual blood flow and acute heart failure on MSI, and highlights current technological challenges and future research directions.

CAG combining MPI after PCI can be used to obtain MSI. MSI is linked to long-term cardiac function. The amount of antegrade flow before PCI and the initial cardiac function upon admission significantly influence MSI.

This study aimed to assess the effectiveness and precision of a deep learning-based model in forecasting the early response of HCC patients to TACE.

A comprehensive review of HCC-TACE data involving 111 patients with HCC was carried out, encompassing both pre-TACE MR images (captured before the first TACE) and post-TACE imaging (acquired between 30 and 60 days following TACE). Based on the mRECIST criteria, patients were divided into two cohorts: a training dataset (91 subjects, 645 images) and a test dataset (20 subjects, 155 images). A deep learning-based model utilizing LeNet architecture with an attention mechanism was developed, targeting the prediction of HCC patients' response to TACE. The robustness and accuracy of the model were examined via ROC curves and confusion matrices.

Post-TACE treatment, 56 patients (50.5%) manifested an objective response (CR+PR), whereas 55 patients (49.5%) exhibited no response (SD+PD). Concerning the model's predictive ability for TACE response, the AUC was found to be 0.760 in the training dataset and 0.729 in the test dataset. The model's prediction accuracy was further corroborated by the confusion matrix, revealing an average accuracy of 70.7% in the training dataset and 72.3% in the test dataset.

Implementing a deep learning-based model using MRI data is potent for forecasting HCC patients’ response to TACE treatment. The novel LeNet model with the attention mechanism conceived in this study contributes valuable insights that can guide the formulation of effective treatment strategies.

Unilateral upper ureteral obstruction is one of the most common causes of acute kidney function impairment. Grading perirenal changes secondary to acute unilateral upper urinary tract obstruction (AUUTO) with multidetector spiral computed tomography (MDCT) and exploring its association with kidney function are useful for diagnosing and assessing damage to the ipsilateral kidney. However, the correlation between renal function impairment and the severity of perinephric changes secondary to AUUTO has not been reported.

This study aimed to investigate the association of perirenal changes secondary to AUUTO with hydronephrosis and serum creatinine levels, as well as white blood cell counts.

This retrospective study included 376 patients with acute unilateral upper ureteral obstruction, all of whom were subjected to MDCT scans. They were classified into four grades (0-III) according to their perirenal changes on MDCT images. The severity of hydronephrosis was classified into four grades based on MDCT scans. The serum creatinine level and leukocyte counts were compared among the MDCT grade groups, and logistic regression analysis was conducted.

Among 376 patients, 77 (20.5%), 103 (27.4%), 140 (37.2%), and 56 (14.9%) cases were graded into MDCT 0, I, II, and III, respectively. The proportions of patients who had normal kidneys in MDCT 0, I, II, and III were 20 (26.0%), 10 (9.7%), 11(7.9%), and 3 (5.4%), respectively. The proportions of patients who had mild hydronephrosis in MDCT 0, I, II, and III were 55 (71.4%), 83 (80.6%), 118 (84.2%), and 46 (82.1%), respectively. The proportions of patients who had moderate and severe hydronephrosis in MDCT 0, I, II, and III were 2(2.6%), 10 (9.7%), 11 (7.9%), 7 (12.5%), respectively. Serum creatinine levels and white blood cell counts were significantly different among the MDCT grade groups (P < 0.001). Univariate and multivariate logistic regression analyses indicated that the serum creatinine level and white blood cell counts were positively associated with the MDCT grades (P < 0.001).

Perinephric changes secondary to AUUTO on MDCT images were associated with the degree of obstruction. The severity of perinephric changes can reflect the functional impairment in the ipsilateral kidney. The MDCT grades may aid clinicians in assessing renal function impairment early in patients with AUUTO, which may help patients receive early intervention and avoid the potential risk of infection and deterioration of renal function.

The incidence of Alzheimer’s disease is rising with the increasing elderly population worldwide. While no cure exists, early diagnosis can significantly slow disease progression. Computer-aided diagnostic systems are becoming critical tools for assisting in the early detection of Alzheimer’s disease. In this systematic review, we aim to evaluate recent advancements in computer-aided decision support systems for Alzheimer’s disease diagnosis, focusing on data modalities, machine learning methods, and performance metrics.

We conducted a systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Studies published between 2021 and 2024 were retrieved from PubMed, IEEEXplore and Web of Science, using search terms related to Alzheimer’s disease classification, neuroimaging, machine learning, and diagnostic performance. A total of 39 studies met the inclusion criteria, focusing on the use of Magnetic Resonance Imaging, Positron Emission Tomography, and biomarkers for Alzheimer’s disease classification using machine learning models.

Multimodal approaches, combining Magnetic Resonance Imaging with Positron Emission Tomography and Cognitive assessments, outperformed single-modality studies in diagnostic accuracy reliability. Convolutional Neural Networks were the most commonly used machine learning models, followed by hybrid models and Random Forest. The highest accuracy reported for binary classification was 100%, while multi-class classification achieved up to 99.98%. Techniques like Synthetic Minority Over-sampling Technique and data augmentation were frequently employed to handle data imbalance, improving model generalizability.

Our review highlights the advantages of using multimodal data in computer-aided decision support systems for more accurate Alzheimer’s disease diagnosis. However, we also identified several limitations, including data imbalance, small sample sizes, and the lack of external validation in most studies. Future research should utilize larger, more diverse datasets, include longitudinal data, and validate models in real-world clinical trials. Additionally, explainability is needed in machine learning models to ensure they are interpretable and reliable in clinical settings.

While computer-aided decision support systems show significant promise in improving the early diagnosis of Alzheimer’s disease, further work is needed to enhance their robustness, generalizability, and clinical applicability. By addressing these challenges, computer-aided decision support systems could play a key role in the early detection of Alzheimer’s disease and potentially reduce health care costs.

Adrenal incidentalomas have increased over the past years. Although there are a lot of studies related to the frequency of adrenal masses and comorbidities, whether patients with functional or nonfunctional adrenal masses have higher risk is still a controversial issue.

A total of 464 patients (female/male: 309/155) with adrenal incidentalomas were evaluated and followed up for 8 years. The patients were divided into 5 subgroups, including Autonomous Cortisol Secretion (ACS), Cushing Syndrome (CS), Pheochromocytoma (Pheo), Non-functional Adrenal Incidentalomas (NFAI), and Primary Aldosteronism (PA).

While 336 (72.4%) of the patients had NFAI, the others suffered from ACS (10.8%), CS (4.3%), Pheo (4.1%), and PA (8.4%), respectively. When comparing biochemical and demographical data, BMI (p=0.77), Hba1c (p=0.495), FPG (p=0.28), LDL (p=0.66), and HDL (p=0.521) were similar among the patients with functional and nonfunctional adrenal masses. The most common comorbidities were hypertension (n=259, 55.8%), diabetes mellitus (n=158, 34.1%), and dyslipidemia (33.4%), respectively. While 84 (32.4%) patients with hypertension had functional adrenal masses, the others (n=175, 67.6%) had non-functional adrenal incidentalomas. In subgroup analyses, hypertension was more common in patients with PA (87.2% vs. 72%, p=0.001) and ACS. In multivariable regression analyses, hypertension (p<0.001), cortisol (p=0.003), and aldosterone (p=0.04) levels were significantly correlated with functionality.

Hypertension was the most common comorbidity in patients with adrenal adenomas, especially in functional adrenal adenomas related to serum cortisol and aldosterone levels.

This study aimed to demonstrate the relationship between hemodynamic changes in head blood flow and headache during the premenstrual period in patients experiencing premenstrual syndrome.

Thirty-two female patients experiencing premenstrual headaches were prospectively examined using carotid and vertebral artery duplex ultrasonography during headache episodes in the premenstrual periods and headache-free periods across two consecutive menstrual cycles. The diameters and areas of both the carotid and vertebral arteries, along with systolic and end-diastolic velocities, pulsatility and resistivity indices, and volumetric flow rates, were measured using grayscale imaging. Total head blood flow was determined as the sum of bilateral common carotid artery and vertebral artery flow volumes. Measurements were compared between participants’ premenstrual and menstrual periods.

A statistically significant difference in the diameter of the left external carotid artery was observed between periods with and without headache during the two consecutive menstrual cycles assessed (p = 0.030). Left external carotid artery (p = 0.019), total external carotid artery (p = 0.028), and total head blood volumes (p = 0.030) were significantly higher when headache was present during the premenstrual period than when headache was absent.

Towards the end of the luteal phase, the total head blood flow and external carotid artery flow were high due to a decrease in peripheral resistance caused by the decline in progesterone and hormonal fluctuations during this period.

Increased flow volume in the external carotid arteries and total head blood flow may be a contributing factor to premenstrual headaches.

Post-hepatic resection liver failure (PHLF) remains one of the most serious complications after hepatic resection, with an overall morbidity rate as high as 32% and an approximate 5% mortality. Previous studies demonstrate the potential of shear wave elastography (SWE) to predict PHLF. This meta-analysis aimed to evaluate the diagnostic accuracy of SWE in identifying liver failure after hepatectomy.

A comprehensive search was performed across PubMed/Medline, Embase, and Web of Science to identify studies assessing the diagnostic accuracy of SWE for predicting PHLF. The combined sensitivity, specificity, and the hierarchical summary receiver operating characteristic curve (HSROC) for SWE in detecting PHLF in liver resection patients. The Quality Assessment of Diagnostic Accuracy Studies tool was used to evaluate the quality of the studies included in the analysis. Heterogeneity was explored through sensitivity analysis, univariable meta-regression and subgroup analysis.

This meta-analysis included a total of 13 studies involving 2985 patients. For quantitative analysis. The combined sensitivities and specificities of SWE for detecting post-hepatectomy liver failure were 0.81 and 0.68, respectively. The HSROC value for SWE was 0.82. Significant heterogeneity (I² = 80.22) was observed in pooled specificity. Meta-regression and subgroup analyses suggest that differences in the proportion of patients with HCC and in the diagnostic criteria for PHLF may account for the observed heterogeneity. For the qualitative analysis, six predictive models based on SWE were included, and their AUCs were 0.80-0.915.

Both SWE alone and SWE-based prediction models appear to accurately detect PHLF and help to categorize patients into high- and low-risk groups. It may also assist surgeons in identifying the best candidates for liver resection and enhancing perioperative management.

An accurate and reliable prognostic model for Nasal Extranodal Natural Killer/T-cell Lymphoma (ENKTL) is critical for survival outcomes and personalized therapy. Currently, there is no Magnetic Resonance Imaging (MRI)- based radiomics analysis in the prognosis model for nasal ENKTL patients.

We aim to explore the value of MRI-based radiomics signature in the prognosis of patients with nasal ENKTL.

A total of 159 nasal ENKTL patients were enrolled and divided into a training cohort (n=81) and a validation cohort (n=78) randomly. Radiomics features from pretreatment MRI examination were extracted, respectively. Then two-sample t-test and Least Absolute Shrinkage and Selection Operator (LASSO) regression were used to select the radiomics signatures and establish the Rad-score. Univariate and multivariate Cox proportional hazards regression models were used to investigate the prognostic value of baseline clinical features and establish clinical models. A radiomics nomogram based on the Rad-score and clinical features was constructed to predict Overall Survival (OS). The predictive efficacy of the three models was evaluated in two cohorts.

A total of 1,345 features were extracted from T2-weighted (T2-w) and Contrast-enhanced T1-weighted (CET1-w) images, respectively, and 1,037 features with Intraclass Correlation Coefficient (ICC) >0.7 were selected. Ultimately, 20 features were chosen to construct the Rad-score, which showed a significant association with OS. The C-indexes of the Rad-score were 0.733 (95% confidence interval (CI): 0.645 to 0.816) and 0.824 (95% CI: 0.766-0.882), respectively, in training and validation cohorts. Through the univariate and multivariate analyses, three independent risk factors for OS were identified: Rad-score (HR: 10.962, 95% CI: 3.417-35.167, P <0.001), lactate dehydrogenase (LDH) level (HR: 3.009, 95% CI: 1.128-8.510, P = 0.028) and distant lymph-node involvement (HR: 2.966, 95% CI: 1.015-8.664, P = 0.047). Patients with distal lymph node involvement and LDH level before treatment were included in the clinical model, which achieved a C-index of 0.707 (95% CI: 0.600–0.814) in the training cohort and 0.635 (95% CI: 0.527–0.743) in the validation cohort.

We integrated the Rad-score and clinical variables to establish a radiomics nomogram, which exhibited a satisfactory prediction performance with the C-indexes of 0.849(95% CI: 0.781-0.917) and 0.931 (95% CI: 0.882-0.980) in two cohorts, respectively. The radiomics nomogram was more accurate in predicting OS in patients with nasal ENKTL than the other two models. Based on the radiomics nomogram, patients were categorized into low-risk and high-risk groups in two cohorts (P all < 0.05). The high-risk group defined by this nomogram exhibited a shorter OS.

The Rad-score was significantly correlated with OS for nasal ENKTL patients. Moreover, the MRI-based radiomics nomogram could be used for risk stratification and might guide individual treatment decisions.

Magnetic resonance imaging can differentiate Alzheimer-type dementia from dementia with Lewy bodies using voxel-based specific regional analysis systems for Alzheimer’s disease and arterial spin labeling, which reveal reduced blood flow from the posterior cingulate gyrus to the precuneus in Alzheimer-type dementia. However, the relationship between voxel-based specific regional analysis system scores and arterial spin labeling remains unclear. To investigate the relationship between brain atrophy scores and arterial spin labeling values in the posterior cingulate precuneus.

Participants with suspected dementia who underwent brain magnetic resonance imaging using a voxel-based regional analysis system were included. They were classified as follows: Group 1 (suspected Alzheimer-type dementia) had atrophy ≥2 in the volume of interest; Group 2 (suspected dementia with Lewy body) had atrophy <2 in the volume of interest and ≥0.2 in the gray and white matter of the dorsal brainstem; and Group 3 included those not meeting these criteria. Correlation values among atrophy within the volume of interest, percentage of atrophic areas, atrophy ratio, percentage of total brain atrophy, age, and maximum arterial spin labeling value at the posterior cingulate precuneus were evaluated.

Groups 1, 2, and 3 comprised 179, 143, and 197 patients, respectively. Arterial spin labeling values at the posterior cingulate precuneus were 77.0±24.4–77.3±25.2, 78.3±81.3–80.2±23.6, and 80.2±22.3–80.4±22.8 mL/min/100 g, respectively. Group 1 had a correlation coefficient between total brain atrophy and arterial spin labeling of –0.189 to–0.214 (P<0.01). Group 2 had a correlation coefficient between total brain atrophy and arterial spin labeling of –0.215 to –0.223 (P<0.01). Group 3 showed no significant correlations. No statistically significant difference was observed in ASL 1 and 2 values between the Alzheimer-type dementia and other groups (ASL 1: 74.5 mL/min/100 g vs. 78.8 mL/min/100 g, P=0.08; ASL 2: 74.8 mL/min/100 g vs. 79.2 mL/min/100 g, P=0.101). No statistically significant difference was observed in ASL 1 and 2 values between the Alzheimer-type dementia and DLB groups (ASL 1: 74.5 mL/min/100 g vs. 69.3. mL/min/100 g, P=0.093; ASL 2: 74.8 mL/min/100 g vs. 78.9 mL/min/100 g, P=0.258).

Reduced blood flow in the posterior cingulate gyrus and precuneus shows only a weak correlation with brain atrophy in both Alzheimer-type dementia and dementia with Lewy bodies. Therefore, it is not a reliable marker for differentiating Alzheimer-type dementia from dementia with Lewy bodies and other groups.

It is necessary to avoid using cerebral blood flow assessment alone when diagnosing dementia.

The synchronous occurrence of primary pure squamous cell carcinoma (SCC) and invasive ductal carcinoma (IDC) of the breast is rare. Accurate identification of synchronous primary malignancies is crucial because their prognosis and treatment differ significantly from recurrent diseases. Herein, we present an unusual case highlighting the synchronous development of primary SCC and IDC in the ipsilateral breast.

A 48-year-old woman presented with a palpable mass in her right breast. Preoperative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) demonstrated an irregularly shaped mass with internal rim enhancement. Surgical resection confirmed IDC of nuclear grade 3 with a high proliferation index (Ki-67: 70%), and the patient underwent adjuvant chemotherapy without radiation. Five months postoperation, a chest computed tomography (CT) revealed a new round-shaped lesion with rim enhancement and relatively circumscribed margins near the previous operation site. Breast ultrasound additionally identified a complex cystic and solid mass with an echogenic rind and increased vascularity. Following total resection, a pure squamous cell carcinoma with prominent keratinization was confirmed.

Accurate and early diagnosis of synchronous multiple primary malignancies from recurrence of the primary tumor is critical for improving prognosis by establishing an appropriate treatment and follow-up plan. Recognizing complex cystic and solid masses with relatively circumscribed margins on radiological imaging can assist clinicians in identifying and managing rare cases where IDC and SCC coexist or appear sequentially within a short period.

Dynamic changes in adenomyotic lesions in animal models have been difficult to observe and evaluate in vivo on a regular basis. Therefore, this study aims to investigate the feasibility of establishing a rat model of adenomyosis through autologous endometrial implantation and to assess the value of magnetic resonance imaging (MRI) for noninvasive evaluation of the model.

Forty rats were randomly divided into two groups (20 rats in the control group, 20 rats in the model group). A rat adenomyosis model was constructed through autologous endometrial implantation. Three months after the modeling surgery, the rats underwent MRI examination, including T2-weighted axial imaging and T1-weighted axial imaging. The thickness of the uterine myometrium and junctional zone was measured. Following the MRI, the rat uterus was sliced for hematoxylin-eosin (HE) staining.

In the model group, lesions of adenomyosis were successfully established in all surviving rats. The myometrium of the rat uterus showed uneven thickening accompanied by scattered spotty T2 hypersignal. The junctional zone appeared as a low-signal band between the endometrium with high signal and the myometrium. The average thicknesses of both the myometrium and the junctional zone were significantly greater in the model group compared to the control group, with the differences reaching statistical significance.

Ectopic endometrium can lead to hyperplasia of the peripheral muscle cells in the myometrium, which is manifested on T2-weighted images as localized thickening and hypo-intensity of the myometrium interspersed with punctiform hyperintensity. Histologically, regions of low signal intensity refer to hyperplasia of smooth muscle, while bright foci on T2-weighted images correspond to ectopic endometrial tissue and cystic dilation of glands. This study proved the noninvasive evaluation of a rat adenomyosis model and described the junctional zone in rats using MRI techniques. Histological examination using HE staining confirmed a higher nuclear-to-cytoplasmic ratio and a more compact cell arrangement in the junctional zone region of rats compared to the outer myometrium, which could explain its hypointensity.

MRI is a valuable method for evaluating the rat adenomyosis model non-invasively. Furthermore, the successful visualization of the junctional zone in the rat uterus using MRI may have potential applications in further evaluating the progression of adenomyosis.

The association between ABO and Rh blood groups and diseases is an intriguing topic that continues to be studied, but their potential influence on mandibular asymmetry has not been explored. Temporomandibular joint (TMJ) disorders are multifactorial, and subtle anatomical variations may be linked to genetic predispositions. Our study aims to investigate the relationship between ABO and Rh blood groups and mandibular condylar and ramal asymmetries in a healthy adult Turkish population.

This study included 149 adult patients (67 males, 82 females) who had no history of systemic diseases, craniofacial deformities, or TMJ-related complaints. Asymmetry was assessed in panoramic radiographic images using a formula developed in a previous study. The chi-square and Kruskal-Wallis tests were used to analyze differences among ABO groups while the Mann-Whitney U test was used for Rh groups.

No significant difference was found in terms of gender distribution, Rh factor or age between ABO or Rh groups. However, there was a significant difference in condylar asymmetry index (CAI) between ABO groups (p 0.05). Pairwise comparisons revealed that individuals with AB blood type exhibited significantly higher CAI values compared to those with B blood type. No statistically significant differences in asymmetry indices were observed between Rh groups.

The findings of our study indicate the existence of a significant relationship between blood groups and asymmetry indices in a healthy population. The significant differences in condylar asymmetry between AB and B blood groups indicate a possible association between blood type and mandibular anatomical variations, rather than a causal relationship. Further studies are needed to confirm these findings and to understand the underlying mechanisms of the relationship between blood groups and mandibular asymmetry.

The evaluation of the left atrial (LA) by imaging is becoming increasingly essential due to its significant role in numerous diseases. This study aimed to analyze and summarize research on LA imaging in the past 20 years through bibliometric analysis and offer insights into future research prospects.

The Web of Science (WOS) core collection database was retrieved for literature in LA imaging research from 2004 to 2023. Subsequently, the literature was processed and visualized by the VOSviewer and CiteSpace. VOSviewer was used to create cooperation networks for countries/regions and institutions. CiteSpace was used to analyze burst keywords in citation analysis.

A total of 3664 articles published in this field between January 2004 and December 2023 were analyzed. The number of published articles is increasing year by year. The USA contributed the most articles (1072). Hugh Calkins (44) was the most productive author with the highest publications.

Over the past 20 years, research on LA imaging has grown rapidly. The results of the present study provide insights into the field’s status and indicate the research hotspots. In recent years, research on left atrial appendage occlusion (LAAO) and LA strain has been notably focused, which is expected to remain a prominent topic in future research.

The sphenoid sinus is an important access point for trans-sphenoidal surgeries, but variations in its pneumatization may complicate surgical safety. Deep learning can be used to identify these anatomical variations.

We developed a convolutional neural network (CNN) model for the automated prediction of sphenoid sinus pneumatization patterns in computed tomography (CT) scans. This model was tested on mid-sagittal CT images. Two radiologists labeled all CT images into four pneumatization patterns: Conchal (type I), presellar (type II), sellar (type III), and postsellar (type IV). We then augmented the training set to address the limited size and imbalanced nature of the data.

The initial dataset included 249 CT images, divided into training (n = 174) and test (n = 75) datasets. The training dataset was augmented to 378 images. Following augmentation, the overall diagnostic accuracy of the model improved from 76.71% to 84%, with an area under the curve (AUC) of 0.84, indicating very good diagnostic performance. Subgroup analysis showed excellent results for type IV, with the highest AUC of 0.93, perfect sensitivity (100%), and an F1-score of 0.94. The model also performed robustly for type I, achieving an accuracy of 97.33% and high specificity (99%). These metrics highlight the model's potential for reliable clinical application.

The proposed CNN model demonstrates very good diagnostic accuracy in identifying various sphenoid sinus pneumatization patterns, particularly excelling in type IV, which is crucial for endoscopic sinus surgery due to its higher risk of surgical complications. By assisting radiologists and surgeons, this model enhances the safety of transsphenoidal surgery, highlighting its value, novelty, and applicability in clinical settings.

Rheumatoid arthritis (RA) is a systemic autoimmune disorder primarily characterized by joint degradation, with consequential cardiovascular ramifications significantly impacting patient mortality rates.

We systematically searched for full-text English-language journal articles from 1973 to 2025 in the PubMed and Web of Science databases. Utilizing keywords such as “Rheumatoid Arthritis,” “Autoimmune Diseases,” “Pathophysiology,” “Heart,” “Cardiac,” and “Echocardiography” to narrow the search results. Articles related to the evaluation of heart diseases in rheumatoid arthritis by echocardiography were included, while those with insufficient data or low data quality were excluded. Study quality was assessed using the CASP Quantitative Checklist (2018 version), and data were synthesized through thematic content analysis.

We included 52 studies in this review after the primary analysis. The results show that traditional echocardiography can identify organic changes in the heart and ventricular function impairment of patients with rheumatoid arthritis. New ultrasound techniques, such as speckle tracking and pressure-strain loops, can detect ventricular function impairment earlier than traditional echocardiography.

Echocardiography provides complementary diagnostic information for rheumatoid arthritis cardiac involvement through structural and functional assessment, yet limitations remain. Future work should establish multimodal ultrasound frameworks and develop AI-driven analytical platforms to enhance early detection and precision management.

The continuous progress of ultrasound technology has significantly improved the accuracy of assessing cardiac damage in patients with rheumatoid arthritis, and it has become an essential examination method for screening heart diseases in such patients, providing strong support for early diagnosis.

Unlike its well-established role in lung cancer staging, positron emission tomography /computed tomography (PET/CT)'s role in guiding lung biopsies remains unclear and underutilized, despite its potential to distinguish metabolically active regions from areas of necrosis or fibrosis within lesions.

This study aims to assess the diagnostic efficacy of PET/CT-aided versus conventional CT-guided lung biopsy by comparing the incidences of non-diagnostic results, false results, and complications.

Studies comparing PET/CT-aided and conventional CT-guided lung biopsy were identified through an intensive search of PubMed, Embase, and the Cochrane Library. Data on nondiagnostic results, false results, and complications were extracted. Risk ratios (RRs) with 95% confidence intervals (CIs) were calculated using a random-effects model.

Seven studies involving 1,661 procedures were included. PET/CT-aided lung biopsy significantly reduced nondiagnostic results compared to conventional CT-guided biopsy (2.8% vs. 9.1%; pooled RR: 0.38, 95% CI: 0.20–0.70, P = 0.002). False results were also significantly fewer in the PET/CT-aided group (6.5% vs. 17.0%; pooled RR: 0.48, 95% CI: 0.35–0.65, P < 0.001). There was no statistically significant difference in overall complication rates (28.1% vs. 32.5%; pooled RR: 0.92, 95% CI: 0.77–1.10, P = 0.352), while PET/CT-aided biopsy showed a slight tendency toward fewer major complications (0.9% vs. 1.7%; pooled RR: 0.67, 95% CI: 0.30–1.44, P = 0.303).

PET/CT-aided CT-guided lung biopsy offers advantages over conventional CT-guided lung biopsy by significantly reducing nondiagnostic and false results, without significant differences in the risk of complications.

This study evaluated the impact of Low-Intensity Pulsed Ultrasound (LIPUS) on bone radio density in patients undergoing orthodontic treatment with clear aligners, aiming to enhance bone remodeling and improve treatment stability.

This retrospective study included 68 participants divided into two groups: 34 treated with LIPUS and 34 in a control group. Bone radio density was measured using Hounsfield units from CBCT scans before and after treatment. Statistical analyses included Mann-Whitney U tests and paired t-tests.

The average age was 29.85 ± 14.85 years in the control group and 36.29 ± 12.78 years in the LIPUS group. Bone radio density in the upper arch of the LIPUS group significantly increased from 444.6 HU to 751.3 HU (p < 0.001), while the control group showed a slight decrease in the upper arch (657.4 HU to 650.5 HU, p = 0.86). In the lower arch, a similar trend was observed in the LIPUS group, with an increase from 767.7 HU to 823.4 HU (p = 0.17), though not statistically significant. There were no significant differences in post-treatment ABO DI scores between groups, suggesting equivalent effectiveness in achieving orthodontic outcomes.

LIPUS with clear aligners seems promising in enhancing bone radio density, indicating an improved bone remodeling effect. This highlights LIPUS's potential as a beneficial adjunct in orthodontic treatments.