Search Results (882)

Atrial fibrillation (AF) and heart failure (HF) frequently coexist and mutually worsen prognosis, creating a complex clinical scenario in which treatment decisions are increasingly imaging driven. Catheter ablation has emerged as a pivotal rhythm control strategy in selected patients with HF, but careful phenotyping of the atrial and ventricular substrate is essential to balance potential benefits against procedural risk and the likelihood of durable sinus rhythm. In this narrative review, we summarize the role of multimodality imaging across the entire AF care pathway in patients with HF, from candidate selection to intraprocedural guidance and post-ablation follow-up. Ultrasound imaging remains the cornerstone of pre-procedural assessment. Cardiac computed tomography (CCT) refines anatomical characterization of the left atrium, pulmonary veins, and left atrial appendage. Cardiovascular magnetic resonance (CMR) offers comprehensive tissue characterization of atrial and ventricular fibrosis, allowing distinction between atrial primary and atrial secondary AF phenotypes and informing expectations of reverse remodelling. During ablation, intracardiac echocardiography and transesophageal echocardiography optimize transseptal access, catheter navigation, and complication monitoring, and they are particularly relevant with contemporary Pulsed Field Ablation systems. In follow-up, echocardiography, CCT, and CMR are pivotal for quantifying structural reverse remodelling and detecting rare but life-threatening complications such as atrio esophageal fistula and pulmonary vein stenosis. An integrated, multimodality, substrate-based imaging strategy is therefore crucial to personalize rhythm versus rate control decisions and to guide safe, effective ablation in patients with AF and HF. Full article

Colorectal cancer (CRC) remains the third most common malignancy worldwide and a leading cause of cancer mortality, largely driven by metastatic dissemination. Among metastatic routes, lymphatic spread is crucial to determine the prognosis and establish an adequate therapeutic strategy. Lymph node metastasis (LNM) defines stage III disease in the TNM classification, guiding adjuvant chemotherapy and surgical planning. However, nodal staging based on lymphadenectomy and histopathology is invasive, time-consuming, and may lead to overtreatment. Conventional imaging modalities, including computed tomography, magnetic resonance imaging, and endorectal ultrasound, show limited sensitivity and specificity for small or micro-metastatic nodes. Despite multimodal progress, no non-invasive technique reliably identifies malignant nodes in real time. PET–MRI, contrast-enhanced ultrasound, photoacoustic and fluorescence approaches, ICG mapping, and sentinel node biopsy improve detection but remain limited by specificity, cost, or availability. Extranodal extension (ENE) and tumor deposits (TDs) carry major prognostic value, reflecting aggressive biology and association with distant spread. Meanwhile, phylogenetic studies challenge linear dissemination models, indicating that some metastases arise directly from the primary tumor or TDs rather than LNMs. These data support refinement of staging and surgical strategies according to tumor biology rather than purely anatomical criteria. High-frequency quantitative ultrasound (HF-QUS) enables real-time, operator-independent, three-dimensional nodal assessment with reported sensitivity and specificity exceeding 85%. Combined with artificial intelligence and molecular profiling, it may support biologically informed staging, reduce unnecessary surgery, and foster precision oncology. Lymphatic dissemination in CRC offers a platform to merge tumor biology with technological innovation, where advanced imaging, molecular insight, and artificial intelligence may redefine nodal staging toward precision, non-invasive care. Full article

Background: Abdominal pain in hematological patients, particularly during chemotherapy-induced neutropenia, represents a significant diagnostic challenge due to the broad spectrum of potentially life-threatening conditions, including neutropenic enterocolitis (NEC). Computed tomography (CT) is considered the reference imaging modality; however, its use is limited by radiation exposure, and the need for patient transport. Bedside ultrasound (BS-US) may offer a rapid, non-invasive, and repeatable alternative. Methods: This prospective study compared BS-US and CT in 65 hematological patients presenting with acute abdominal pain. Concordance between the two modalities was evaluated in terms of intestinal site localization, bowel wall thickness (BWT), and final diagnosis. Diagnostic agreement was assessed using Cohen’s kappa coefficient, and additional diagnostic accuracy metrics—including sensitivity, specificity, positive predictive value, and negative predictive value—were calculated. BWT measurements were analyzed using Bland–Altman methods. Results: A high level of agreement was observed between BS-US and CT in both intestinal localization and final diagnosis. Agreement for intestinal site localization was good (Cohen’s κ = 0.964), as was diagnostic concordance (Cohen’s κ = 0.962), and using CT as the reference standard, BS-US showed uniformly good diagnostic performance across all evaluated conditions, with sensitivity, specificity, PPV, and NPV consistently reaching 1.00 and confirming strong agreement between BS-US and CT. These findings were consistent across different clinical settings (hematology unit and Intensive Care Unit) and independent of body mass index. In NEC cases, BWT measurements showed strong concordance between CT and BS-US, with only 4.6% of values outside the limits of agreement in Bland–Altman analysis. Conclusions: BS-US demonstrated a good agreement with CT and proved to be a reliable, safe diagnostic tool in hematological patients with acute abdominal pain. These findings indicate that bedside ultrasound represents a valuable and safe diagnostic tool in neutropenic hematological patients with acute abdominal pain, providing crucial information in a clinically fragile population that may not always be suitable for CT due to their unstable condition. While our study is hypothesis-generating, the role of BS-US in this setting emerges as a reasonable, evidence-supported hypothesis that warrants further prospective evaluation. Full article

Transbronchial lung cryobiopsy (TBLC) is increasingly used as a minimally invasive approach for tissue acquisition in the evaluation of interstitial lung disease (ILD), serving as an alternative to surgical lung biopsy (SLB) within multidisciplinary diagnostic pathways. Despite its growing adoption, variability in diagnostic yield and complication rates highlight the importance of procedural technique, probe selection, and freezing parameters. This narrative review summarizes the current landscape of TBLC, with emphasis on factors that influence diagnostic performance and safety, including procedural considerations involving endobronchial balloon blockade (EBB), radial probe endobronchial ultrasound (RP-EBUS), and cone-beam computed tomography (CBCT) for biopsy localization and airway management. Much of the existing experience is based on conventional cryoprobes, including 2.4 mm and 1.9 mm devices, typically used with freezing times of several seconds. While these approaches have defined the current role of TBLC in ILD, outcomes remain variable across centers, prompting continued refinement of procedural strategies to improve consistency. More recently, attention has expanded to include a broader range of smaller cryoprobe sizes—1.7 mm and 1.1 mm. Overall, this review provides a framework for understanding contemporary TBLC practice and highlights key areas where further study is needed to better define optimal technique and improve consistency in clinical outcomes. Full article

Myocardial infarction with non-obstructive coronary arteries (MINOCA) accounts for approximately 5–15% of all myocardial infarctions and disproportionately affects women. Once treated as a diagnosis of exclusion, MINOCA is now recognised as a heterogeneous, mechanism-based syndrome encompassing atherosclerotic plaque disruption, epicardial and microvascular vasospasm, microvascular dysfunction, coronary thromboembolism, and spontaneous coronary artery dissection (SCAD). Despite the absence of obstructive disease, it carries substantial morbidity and mortality, underscoring the need for accurate aetiological characterisation and tailored therapy. Our aim is to review the contemporary evidence of the role of advanced imaging modalities—cardiac magnetic resonance imaging (CMR), optical coherence tomography (OCT), intravascular ultrasound (IVUS) and invasive functional testing—in the diagnosis, prognostic stratification, and therapeutic guidance of patients with MINOCA. CMR is the non-invasive reference standard for differentiating true ischaemic MINOCA from non-ischaemic mimics such as myocarditis and Takotsubo syndrome, reclassifying the working diagnosis in up to two-thirds of cases. OCT and IVUS provide intracoronary characterisation of culprit substrates that are invisible via angiography, particularly plaque rupture, erosion, intramural haematoma and SCAD, while acetylcholine and adenosine testing identify endothelium-dependent vasospasm and endothelium-independent microvascular dysfunction respectively. Coronary Computed Tomography Angiography (CCTA) could also play an additional role in the diagnosis of epicardial CAD. Each modality additionally carries independent prognostic value, with abnormal findings consistently linked to higher rates of major adverse cardiovascular events. The recently completed PROMISE trial provided the first randomised evidence that stratified, imaging-guided treatment might have some positive impact on angina status and quality of life compared with empirical standard care. In conclusion, advanced imaging has transformed MINOCA from a diagnosis of exclusion into a mechanism-based syndrome amenable to personalised therapy. Broader integration of these modalities into routine practice, supported by further randomised trials, is needed to optimise outcomes. Full article

Neurolymphomatosis (NL), a rare manifestation of non-Hodgkin’s lymphoma affecting the peripheral nervous system, remains a diagnostic challenge. This study aimed to define an optimal diagnostic approach for timely and effective identification of NL. We analyzed 559 NL cases from 231 articles published from 1951 to 2022, examining how patient outcomes correlated with various diagnostic modalities, including magnetic resonance imaging (MRI), computed tomography (CT), [¹⁸F]fluorodeoxyglucose positron emission tomography (FDG-PET), electromyography-nerve conduction studies (EMG-NCS), ultrasound, and tissue biopsy when used individually or in combination. Separate analyses were performed in a mutually exclusive fashion to minimize confounding effects from multiple modalities. The results of this investigation revealed that patients with biopsies had a longer time interval from first treatment to progression (Kruskal–Wallis p < 0.0001), survival from diagnosis (overall survival) (p < 0.0001), and survival from symptom onset (p < 0.0001), but not symptom onset to diagnosis (p = 0.2134). Pairwise comparisons of biopsy plus 2, 3, or 4 diagnostic modalities revealed a positive trend for the combination of biopsy + PET + MRI + EMG-NCS. A majority of patients without biopsy had secondary NL. In this non-biopsied population, no diagnostic modality had a significant correlation with outcome. The data collectively indicate that histological confirmation of NL from biopsy was associated with a positive patient outcome. Management of NL patients requires timely testing using PET, MRI, and EMG-NCS to quickly identify a site for image-guided nerve biopsy. Full article

Background and Clinical Significance: Cardiac and mediastinal angiosarcomas are rare, aggressive malignancies that often present with nonspecific symptoms and pose significant diagnostic challenges. Tumor heterogeneity and necrosis may lead to false-negative biopsy results; Case Presentation: We report a 64-year-old man who initially presented with cardiac tamponade of unclear etiology. Despite an extensive workup, the patient remained asymptomatic for five months before re-presenting with dyspnea and a large mediastinal mass compressing the right heart, along with a lytic rib lesion. Initial ultrasound-guided biopsy of the rib lesion demonstrated a benign vascular proliferation consistent with Masson tumor (intravascular papillary endothelial hyperplasia), which was discordant with aggressive imaging findings. Further evaluation with positron emission tomography–computed tomography (PET-CT) revealed peripheral metabolic activity, and cardiac magnetic resonance imaging (MRI) demonstrated a heterogeneous mass with central necrosis and peripheral enhancement. A repeat CT-guided biopsy targeting the metabolically active region confirmed angiosarcoma, with immunohistochemical staining demonstrating diffuse positivity for ERG, CD31, and CD34. The patient was treated with palliative radiation and paclitaxel-based chemotherapy but experienced rapid clinical decline and transitioned to comfort-focused care; Conclusions: This case highlights the importance of correlating imaging with pathology and emphasizes the risk of sampling error in necrotic tumors. PET-guided biopsy targeting viable tumor regions is essential in cases with discordant findings. Full article

Background: Hydatid disease, caused by Echinococcus granulosus, remains a significant public health concern in endemic regions. This study aimed to evaluate the role of ultrasound in the diagnosis, staging, and clinical management of liver hydatid cysts in the eastern city of Jalalabad, Afghanistan. Method: A cross-sectional study was conducted between February and November 2024 among 159 patients diagnosed with liver hydatid cysts. Demographic, clinical, laboratory, and imaging data were collected. Cysts were classified according to the WHO Informal Working Group on Echinococcosis (WHO-IWGE) and Gharbi systems. Ultrasound findings were compared with computed tomography (CT), and their association with treatment decisions was assessed. Result: A total of 159 patients with liver hydatid cysts were included in the study. Among them, 91 (57.2%) were female, 80 (50.3%) were aged 20–39 years, and 128 (80.5%) resided in rural areas. Most patients presented with a single cyst (144/159, 90.6%), while multiple cysts were observed in 15 (9.4%). The majority of cysts measured 5–9.9 cm in diameter (43.4%), followed by 1–4.9 cm (42.1%) and ≥10 cm (14.5%). According to the WHO-IWGE classification, CE1 (25.8%) and CE4 (24.5%) were the most common stages, followed by CE2 (17.6%), CE3a (13.8%), CE3b (11.3%), and CE5 (7.0%). Common exposure-related factors included dog ownership, poor hygiene practices, and consumption of raw vegetables. Ultrasound accurately identified cyst stages and demonstrated a significant association between WHO-IWGE staging and treatment modality (χ² = 63.56, p < 0.001). Almost perfect agreement was observed between ultrasound and CT for cyst classification (Cohen’s κ > 0.90), although CT provided additional anatomical information in selected complex cases. Conclusions: Ultrasound is an accessible, accurate, and reliable imaging modality for the diagnosis, staging, and management of liver hydatid cysts. In resource-limited settings, it serves as the primary imaging modality for guiding clinical decision-making, with CT reserved for complex or uncertain cases. Full article

Background/Objectives: Early recurrence after curative-intent resection is a major determinant of poor prognosis in hepatocellular carcinoma (HCC). Artificial intelligence (AI)-driven predictive models have emerged to identify patients at high risk of recurrence but remain incompletely synthesized for early recurrence specifically. This review aimed to identify and appraise AI-driven models predicting early recurrence after surgical resection. Methods: PubMed/MEDLINE, Scopus and Web of Science were searched from inception to November 2025. Eligible studies developed and evaluated AI-driven models predicting early recurrence (≤24 months) after curative-intent hepatectomy as first-line treatment for HCC. Risk of bias and applicability were assessed using PROBAST+AI, and findings were synthesized narratively due to methodological heterogeneity. The review was registered in PROSPERO. Results: Thirty-six studies involving 14,716 patients were included. Most studies originated from China (33/36, 91.7%), were single-center (27/36, 75%), and retrospective (35/36, 97.2%). Magnetic resonance imaging (MRI) was the predominant imaging modality (15/36, 41.7%), followed by computed tomography (CT) (11/36, 30.6%) and ultrasound (US)/contrast-enhanced ultrasound (CEUS) (6/36, 16.7%). Three studies developed non-imaging models, and one combined CT and MRI. In within-study comparisons, multimodal models generally showed better discrimination than unimodal approaches. Peritumoral, habitat-based, and multiphasic strategies appeared promising. However, external validation was reported in only 6/36 studies (16.7%), calibration and decision-curve analysis were inconsistently reported, and most studies had high risk of bias. Conclusions: AI-driven models show potential to predict early recurrence of HCC after curative-intent resection. Nevertheless, evidence remains limited by methodological heterogeneity and restricted geographical diversity, while clinical utility remains inconsistently evaluated, and no model has yet been generalized in clinical practice. Prospective multicenter studies with standardized outcomes, transparent reporting, and external validation are needed for clinical implementation. Full article

The coronary arteries are a pair of arteries that branch off from the aorta and encircle the heart, providing oxygenated blood to the myocardium. Although coronary artery atherosclerosis remains a main cause of morbidity and mortality worldwide, coronary artery anomalies (CAAs) are increasingly recognized as a clinically relevant cause of ischemic events and can be subdivided into origin, course, or termination anomalies. The aim of this narrative review is to summarize the cross-sectional diagnostic imaging and clinical background of CAAs. Full article

Background/Objectives: Accurate tissue diagnosis of small pulmonary nodules remains technically challenging with conventional bronchoscopic techniques. Radial probe endobronchial ultrasound-guided transbronchial lung cryobiopsy (RP-EBUS–guided TBLC) with a guide sheath (GS) may improve diagnostic yield; however, target instability during cryobiopsy remains a limitation. We aimed to evaluate the diagnostic yield of RP-EBUS-guided TBLC with a GS for pulmonary nodules < 3 cm that were suspected of malignancy. Methods: This retrospective observational study included patients who underwent RP-EBUS-guided TBLC with a GS for lung lesions suspected of malignancy on computed tomography between 1 February 2024 and 31 December 2025 in South Korea. After the target lesion was identified, the bronchoscope was inserted and fixed within the segment; its position was maintained while RP-EBUS was withdrawn, and lesion stability during respiration was confirmed. Results: A total of 99 patients were included in the final analysis. After patients with an indeterminate diagnosis were excluded, the final diagnostic yield was 83.2%. The sensitivity and specificity were 78.9% and 100.0%, respectively. Pneumothorax occurred in 6.0% (6/99) of patients. Bleeding of grade 3 or higher was observed in two patients, and a Fogarty balloon catheter was preemptively used in five patients at the operator’s discretion. In multivariable logistic regression analysis, the computed tomography bronchus sign was identified as the only significant factor associated with pathological confirmation (odds ratio, 6.090; p = 0.005). Conclusions: RP-EBUS-guided TBLC with a GS provided an acceptable diagnostic yield and safety profile, even in small pulmonary nodules < 3 cm. Full article

Background/Objectives: Given rising lung cancer incidence and limited data on pulmonologist-performed ultrasound-guided transthoracic core biopsy (US-TTCB), in this study, we evaluated diagnostic yield and safety for pleural or pulmonary lung masses, using Clavien–Dindo classification to standardize complication reporting. Methods: We retrospectively reviewed single-center pulmonologist-performed US-TTCB using a MEDONE biopsy gun with a 16 G/18 G Tru-Cut needle between January 2019 and December 2025. The primary endpoints were diagnostic yield, defined as specific malignant or benign histology, and complication rate. Non-diagnostic results were assessed using available clinical/imaging follow-up. Univariate analyses screened candidate correlates, and a prespecified computer tomography (CT)-completed subanalysis (n = 67) used multivariable logistic regression and receiver operating characteristic (ROC) analysis to assess CT lesion size discrimination. Results: Diagnostic yield was 84.2% (202/240); complications occurred in 12.1% (29/240), including one Clavien–Dindo Grade III event (0.4%). In the CT-completed subset (n = 67), diagnostic yield was independently associated with CT lesion size (aOR 1.03/mm, 95% CI 1.00–1.05; p = 0.022) and Chronic Obstructive Pulmonary Disease (COPD) (aOR 2.30, 95% CI 1.06–4.96; p = 0.034); CT lesion size showed an area under the curve (AUC) of 0.717 for predicting yield. Diagnostic yield remained stable over time (84.2% in first vs. second half; p = 1.00), with no association between case order and yield (OR 0.999; p = 0.64). Conclusions: US-TTCB of pleural/pulmonary masses achieved a high diagnostic yield with minimal major complications. Large CT dimension and COPD were associated with higher diagnostic success, and CT size provided fair discrimination for predicting yield; findings should be interpreted in the context of the retrospective single-center design and the restricted CT-completed subset. Full article

Background: Respiratory diseases (RDs), including asthma, COVID-19, chronic obstructive pulmonary disease (COPD), and pneumonia, remain a major global health challenge, contributing substantially to global morbidity and mortality. Conventional diagnosis relies heavily on clinicians’ expertise to interpret respiratory sounds and radiographic images, a process that can be subjective, time-consuming, and prone to inter-observer variability. Recent advances in artificial intelligence (AI) and machine learning (ML) have enabled automated diagnostic approaches that can improve the efficiency, consistency, and scalability of respiratory disease detection. However, existing research remains fragmented across different data modalities. Methods: This review systematically analyzes recent studies on AI-based respiratory disease detection using both visual modalities (e.g., chest X-rays, computed tomography (CT) scans, and ultrasound) and audio modalities (e.g., cough and breath sounds). To provide a comprehensive perspective, the reviewed literature is organized using a unified taxonomy that categorizes existing approaches into three main groups: audio-based, visual-based, and audio–visual-based methods. In addition, two conceptual frameworks are proposed to illustrate representative pipelines for audio-based and visual-based respiratory disease classification. Results: The analysis reveals that most existing studies focus on single-modality approaches, while multimodal integration remains relatively underexplored. Only a limited number of studies combine audio and visual data within unified frameworks, primarily due to the scarcity of synchronized multimodal datasets collected from the same patients. The proposed taxonomy and conceptual frameworks provide a structured basis for comparing existing methods, identifying methodological trends, and highlighting key research gaps in multimodal respiratory disease detection. Conclusions: Future research should prioritize the development of multimodal datasets, robust evaluation protocols, and interpretable and lightweight AI models suitable for real-world clinical deployment. Advancing multimodal integration has the potential to significantly enhance the accuracy, reliability, and clinical applicability of AI-driven respiratory disease diagnosis systems. Full article

Background: Radiology underpins diagnosis and treatment across pediatrics, yet most artificial intelligence (AI) tools are developed for adults and validated on adult datasets only. Of more than 200 AI systems cleared by the United States (U.S.) Food and Drug Administration (FDA), only about 3% include pediatric validation. Because children differ from adults in anatomy, physiology, pathology, epidemiology, and imaging protocols, adult-trained models often perform sub-optimally in pediatric settings. Methods: A narrative review of peer-reviewed literature from 2000 to 2025 was conducted using PubMed, MEDLINE, Google Scholar, and Scopus. Studies involving AI applications in pediatric X-ray, ultrasound, computed tomography (CT), magnetic resonance imaging (MRI), echocardiography, and point-of-care ultrasound with quantitative performance metrics were included. Findings were synthesized by imaging modality, clinical task, and differences between high-income countries (HICs) and low- and middle-income countries (LMICs). Results: AI demonstrated strong performance across multiple pediatric imaging tasks. In X-ray interpretation, AI detected fractures with area under the curve (AUC) values up to 0.96 (sensitivity, 90.8%; specificity, 88.7%). Pneumonia classification achieved 76.5% accuracy, and foreign body aspiration detection showed 95.3% specificity in HICs. In ultrasound, AI improved junior sonographers’ detection of intussusception (AUC 0.857 to 0.966) and reduced scan time by more than 50%. AI-assisted bone age estimation achieved a mean error of 0.39 years. In echocardiography, AI-derived ejection fraction showed excellent agreement with experts’ interclass correlation coefficient (ICC 0.983), and AI support improved atrioventricular septal defect detection (84.4% to 86.5%). In MRI, the use of AI enhanced lesion detection and supported quantitative analysis. Deep-learning models trained on routine T1- and T2-weighted sequences predicted liver stiffness across multi-site datasets, while advanced neuroimaging pipelines improved the identification of subtle epileptogenic lesions that are often missed on conventional pediatric MRI. However, adult-trained models showed limited generalizability to children. Still, excluding children under the age of two years improved the reading accuracy of pediatric chest X-rays (CXRs) by adult-trained models from 88% to 97%. AI faces challenges beyond the development of age-specific models. Substantial heterogeneity, limited pediatric-specific datasets, and unresolved medicolegal responsibility further restrict adoption worldwide. Challenges are amplified in LMICs, where unstable electricity, limited radiology resources, weak digital infrastructure, and scarce pediatric providers limit implementation. Additionally, many large language models underperform and lack inclusive algorithms suitable for pediatric radiology in many LMICs. Conclusions: AI can enhance diagnostic accuracy, efficiency, and access to pediatric imaging, particularly in resource-limited settings, through task-shifting and decision support. However, it cannot replace pediatric radiologists as of today. Safe adoption requires pediatric-specific model development, standardized validation metrics, diverse datasets that include LMIC populations, stronger digital infrastructure, robust radiologist training in AI capabilities, and the establishment of clear guidelines and medicolegal policies. Full article

Objectives: Low-intensity pulsed ultrasound (LIPUS) has been widely utilized as a biophysical modality accelerating fracture healing, particularly in bones undergoing endochondral ossification. However, its efficacy in facilitating intramembranous ossification remains unclear. This study aimed to evaluate the effects of LIPUS and autologous bone (AB) on bone healing in a critical-size bone defect (CSBD) model of the rat calvaria. Methods: We performed micro-computed tomography (micro-CT) and immunohistochemical TNF-α analysis on bone specimens to assess osteogenesis. Results: Micro-CT demonstrated significant increases in newly formed bone on day 30 compared with days 7 and 15 across all groups (p < 0.001). The highest bone volume was observed in the AB group (26.83%), followed by the LIPUS group (23.74%), and the lowest in the control (15.85%). Immunohistochemical analysis revealed significantly higher TNF-α expression on day 7 in the control group (172.0 ± 1.1) than in the AB (133.8 ± 0.9) and LIPUS (125.2 ± 0.8) groups (p < 0.001). On day 15, TNF-α expression was significantly higher in the LIPUS group (137.7 ± 1.3) than in both the AB (134.2 ± 1.8) and control (126.6 ± 2.2) groups (p < 0.001). At day 30, TNF-α levels in the LIPUS group (147.6 ± 1.9) remained significantly higher than in the control group (115.8 ± 0.9) (p < 0.001), with no significant difference compared to the AB group (146.3 ± 0.8). Conclusions: Although AB grafting achieved the greatest bone volume, LIPUS demonstrated considerable regenerative potential and may represent a promising non-invasive therapeutic approach to enhance intramembranous bone regeneration. Full article