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Background: Extracranial arteriovenous malformations (AVMs) are rare congenital vascular anomalies that often require endovascular treatment due to symptoms such as pain, bleeding, or functional impairment. Endovascular strategies include arterial, venous, or combined embolization approaches; however, recurrence remains a major challenge. We retrospectively evaluate the technical success, safety, and clinical outcomes of arterial-only versus combined arterial and venous embolization for the treatment of extracranial AVMs.

Materials and methods: This single-center retrospective study included 14 patients (mean age 31.8 ± 21.7 years; 64% female) with symptomatic extracranial AVMs (Schobinger stage II) treated between 2017 and 2023. AVMs were classified angiographically (Yakes classification) and treated with embolization via arterial or combined access routes. The primary endpoint was technical success (defined as angiographic nidus occlusion), while secondary endpoints included clinical recurrence and procedure-related complications. Follow-up included clinical and Doppler ultrasound assessments.

Results: Nine patients (64%) underwent arterial embolization alone; five (36%) received combined arterial and venous embolization, including Lauromacrogol injection via direct puncture. Technical success was achieved in all cases (100%). Clinical recurrence occurred in two patients (14%), both from the arterial-only group. One major complication (tongue ischemia) occurred in a single patient (7%). No complications or recurrences were observed in the combined treatment group. Statistical analysis showed no significant difference in recurrence or complication rates between groups.

Objective: This ex vivo study aimed to evaluate the influence of different acquisition protocols, combining voxel size and field of view (FOV), across four cone-beam computed tomography (CBCT) systems, on the accuracy of alveolar bone level measurements for periodontal assessment.

Materials and methods: A dry human mandible was used, with standardized radiopaque markers placed on the cementoenamel junction (CEJ) of the buccal-mesial and buccal-distal aspects of teeth 34 and 43. CBCT scans were performed using four systems-Veraview^® X800, OP300 Pro^®, I-CAT Next Generation^®, and Orthophos XG^®-applying various combinations of field of view (FOV) and voxel resolution available in each device. Reference measurements were obtained in situ using a digital caliper. CBCT images were exported in DICOM format and analyzed with OnDemand3D software (version 4.6) to obtain paracoronal sections. Linear measurements from the CEJ to the alveolar crest were recorded in triplicate and compared to the gold standard using ANOVA and the Dunnett test (α = 0.05).

Results: Protocols with smaller voxel sizes and limited FOVs generally yielded measurements closer to the gold standard. However, some larger-FOV protocols with intermediate voxel sizes also achieved comparable accuracy. Among the systems, the I-CAT showed lower agreement within in situ measurements, while others demonstrated reliable performance depending on the acquisition parameters.

Conclusions: The findings suggest that CBCT protocols with smaller voxel sizes and reduced FOVs can enhance measurement accuracy in periodontal bone assessments. Nevertheless, intermediate protocols may offer a balance between diagnostic quality and radiation exposure, aligning with the ALADA principle. This study reinforces the need for standardized acquisition parameters tailored to periodontal imaging.

Background/objectives: The relationship between upper trapezius muscle stiffness and choroidal circulatory dynamics remains unclear. This study aimed to examine changes in upper trapezius muscle stiffness and choroidal circulatory dynamics before and after trapezius muscle self-stretching.

Methods: Eighteen healthy adults in their 20s (median age ± standard error: 21.0 ± 4.9 years) and eight healthy adults in their 40s (age: 43.0 ± 15.2 years) were included. Intraocular pressure (IOP); systolic, diastolic, and mean blood pressure (BP); heart rate (HR); ocular perfusion pressure (OPP); and salivary alpha-amylase (sAA) activity-as an indicator of autonomic nervous system function-were measured at baseline and after trapezius muscle self-stretching. Upper trapezius muscle stiffness was assessed using ultrasound strain elastography, whereas choroidal circulation was evaluated using laser speckle flowgraphy to determine the mean blur rate (MBR), a relative measure of macular blood flow velocity.

Results: Significant reductions in systolic and mean BP; OPP; sAA activity; and MBR were observed after trapezius muscle self-stretching in both groups; however, no significant changes were found in IOP and HR. A significant decrease in upper trapezius muscle stiffness was observed after self-stretching only in the 20-year-old group.

Conclusions: In healthy adults in their 20s and 40s, trapezius muscle self-stretching may enhance parasympathetic nervous system activity, resulting in decreased systemic and choroidal circulatory parameters. However, the reduction in muscle stiffness observed only in younger participants suggests that short-term self-stretching may be less effective in reducing trapezius muscle stiffness with advancing age.

Objectives: To evaluate the agreement between AI-CAD-guided mammographic and MRI measurements of tumor size and T stage in breast cancer patients being considered for neoadjuvant chemotherapy (NAC). Methods: This retrospective study included 144 women (mean age, 52 ± 11 years) with invasive breast cancer who subsequently received NAC and underwent both AI-CAD mammography (score ≥ 10) and pre-treatment MRI. Tumor sizes from AI-CAD contours were compared with MRI using Pearson correlation, intraclass correlation coefficients (ICCs), and Bland-Altman analysis. Concordance was defined as a ±0.5 cm difference. The contour showing the highest agreement was used to compare T stage with MRI using weighted kappa. Results: The mean AI-CAD abnormality score was 86.3 ± 22.2. Tumor sizes on mammography were 3.0 ± 1.2 cm (inner), 3.8 ± 1.5 cm (middle), and 4.8 ± 2.2 cm (outer), while the MRI-measured tumor size was 4.0 ± 1.9 cm. The middle contour showed the strongest correlation with MRI (r = 0.897; ICC = 0.866), the smallest mean difference (-0.19 cm; limits of agreement, -1.87 to 1.49), and the highest concordance (61.1%). Agreement was higher in mass-only lesions than in NME-involved lesions (ICC = 0.883 vs. 0.775; concordance, 70.9% vs. 46.6%). T stage comparison using the middle contour showed substantial agreement with MRI (κ = 0.743 [95% CI, 0.634-0.852]; agreement, 88.2%), with higher concordance in mass-only lesions (93.0%) than NME-involved lesions (81.0%) and more frequent understaging in the latter (17.2% vs. 2.3%). Conclusions: AI-CAD-guided mammographic assessment using the middle contour demonstrated good agreement with MRI for tumor size and T stage, indicating its value as a supportive tool for clinical staging in MRI-limited settings.

Background: Pediatric high-grade glioma (pHGG) is a highly aggressive cancer with unique biology distinct from adult high-grade glioma, limiting the effectiveness of standard treatment protocols derived from adult research.

Objective: The purpose of this report is to present preliminary results from an ongoing pilot study integrating spectroscopic magnetic resonance imaging (sMRI) to guide proton beam therapy and longitudinal imaging analysis in pediatric patients with high-grade glioma (pHGG).

Methods: Thirteen pediatric patients under 21 years old with supratentorial WHO grade III-IV glioma underwent baseline and serial whole-brain spectroscopic MRI alongside standard structural MRIs. Radiation targets were defined using T1-weighted contrast enhanced, T2-FLAIR, and Cho/NAA ≥ 2X maps. Longitudinal analyses included voxel-level metabolic change maps and spatial overlap metrics comparing pre-proton therapy and post-.

Results: Six patients had sufficient longitudinal data; five received sMRI-guided PBT. Significant positive correlation (R² = 0.89, p < 0.0001) was observed between T2-FLAIR and Cho/NAA ≥ 2X volumes. Voxel-level difference maps of Cho/NAA and Choline revealed dynamic metabolic changes across follow-up scans. Analyzing Cho/NAA and Cho changes over time allowed differentiation between true progression and pseudoprogression, which conventional MRI alone struggles to achieve.

Conclusions: Longitudinal sMRI enhanced metabolic tracking in pHGG, detects early tumor changes, and refines RT targeting beyond structural imaging. This first in-kind study highlights the potential of sMRI biomarkers in tracking treatment effects and emphasizes the complementary roles of metabolic and radiographic metrics in evaluating therapy response in pHGG.

Objective: Endocrine disorders, including diabetes mellitus and thyroid dysfunctions, can significantly impact bone metabolism and structure. This study aimed to assess mandibular trabecular architecture in patients with type 1 diabetes mellitus (T1DM), type 2 diabetes mellitus (T2DM), hyperthyroidism, and hypothyroidism using fractal dimension (FD) and histogram analyses (HA), comparing the findings with a healthy control group.

Methods: This retrospective study analyzed panoramic radiographs from 200 individuals, comprising 40 patients in each of the four endocrine disorder groups and 40 healthy controls. Fractal dimension and histogram-based pixel intensity analyses were conducted using ImageJ™ (version 1.53) software. Four standardized regions of interest (ROI) were evaluated on the right mandible, and statistical comparisons were conducted across groups using one-way analysis of variance (ANOVA), t-test, Mann-Whitney U, and Spearman correlation analyses.

Results: Age and gender distributions did not differ significantly between groups. FD analysis revealed a significant reduction at ROI1 in the hyperthyroidism group compared to controls (p = 0.018); however, no other significant FD differences were observed among the remaining groups or ROIs. A significant positive correlation was found between FD and histogram values at ROI1 and ROI2 (p < 0.001), while pixel intensity values did not differ significantly across groups in any ROI.

Conclusion: Although no significant differences were found in diabetic groups, the decreased FD in hyperthyroid patients suggests that FD analysis may be a useful non-invasive method to detect subtle bone alterations. Further research with larger sample sizes and comprehensive biochemical analyses are needed to confirm these findings.

Objectives: to assess the ability of high-performing open-weight large language models (LLMs) in extracting key radiological features from prostate MRI reports.

Methods: Five LLMs (Llama3.3, DeepSeek-R1-Llama3.3, Phi4, Gemma-2, and Qwen2.5-14B) were used to analyze free-text MRI reports retrieved from clinical practice. Each LLM processed reports three times using specialized prompts to extract (1) dimensions, (2) volume and PSA density, and (3) lesion characteristics. An experienced radiologist manually annotated the dataset, defining entities (Exam) and sub-entities (Lesion, Dimension). Feature- and physician-level performance were then assessed.

Results: 250 MRI exams reported by 7 radiologists were analyzed by the LLMs. Feature-level performances showed that DeepSeek-R1-Llama3.3 exhibited the highest average score (98.6% ± 2.1%), followed by Phi4 (98.1% ± 2.2%), Llama3.3 (98.0% ± 3.0%), Qwen2.5 (97.5% ± 3.9%), and Gemma2 (96.0% ± 3.4%). All models excelled in extracting PSA density (100%) and volume (≥98.4%), while lesions' extraction showed greater variability (88.4-94.0%). LLMs' performance varied among radiologists: Physician B's reports yielded the highest mean score (99.9% ± 0.2%), while Physician C's resulted in the lowest (94.4% ± 2.3%).

Conclusions: LLMs showed promising results in automated feature-extraction from radiology reports, with DeepSeek-R1-Llama3.3 achieving the highest overall score. These models can improve clinical workflows by structuring unstructured medical text. However, a preliminary analysis of reporting styles is necessary to identify potential challenges and optimize prompt design to better align with individual physician reporting styles. This approach can further enhance the robustness and adaptability of LLM-driven clinical data extraction.

Background/objectives: Radiotherapy for tumors of the central nervous system (CNS) could be improved by incorporating advanced imaging techniques into treatment planning and response assessment. The objective of this narrative review is to highlight the recent developments in magnetic resonance imaging (MRI) and positron emission tomography (PET) for applications in CNS radiotherapy.

Methods: Recent articles were selected for discussion, covering the following topics: advanced imaging on MRI-linear accelerators for early response assessment in glioma; PET for guiding treatment planning and response assessment in glioma; and contrast-enhanced imaging and metabolic imaging for differentiating tumor progression and radiation necrosis for brain metastasis treatment. Where necessary, searches of scholarly databases (e.g., Google Scholar, PubMed) were used to find papers for each topic. The topics were chosen based on the perception of promise in advancing specific applications of CNS radiotherapy and not covered in detail elsewhere. This review is not intended to be comprehensive.

Results: Advanced MRI sequences and PET could have a substantial impact on CNS radiotherapy. For gliomas, the tumor response to therapy could be assessed much earlier than using the conventional technique of measuring changes in tumor size. Using advanced imaging on combined imaging/therapy devices like MR-Linacs would enable response monitoring throughout radiotherapy. For brain metastases, radiation necrosis and tumor progression might be reliably differentiated with imaging techniques sensitive to perfusion or metabolism. However, the lack of level 1 evidence supporting specific uses for each imaging technique is an impediment to widespread use.

Conclusions: Advanced MRI and PET have great promise to change the standard of care for CNS radiotherapy, but clinical trials validating specific applications are needed.

Background: Cervical foraminal bony stenosis (CFBS) is a common degenerative spinal condition that causes radicular pain and functional impairment in the upper extremities. Accurate and objective diagnosis of CFBS remains challenging due to the absence of standardized morphometric criteria. This study aimed to determine an optimal cut-off value for the cervical foraminal cross-sectional area (CFCSA) at the C5/6 level as a diagnostic indicator of CFBS. Methods: We conducted a retrospective case-control study including 154 patients aged 50 years or older with clinically and radiologically confirmed CFBS and 150 age-matched asymptomatic controls. Cervical spine magnetic resonance imaging (MRI) was performed in all subjects and CFCSA measurements were obtained from sagittal T2-weighted images using a standardized protocol. Group differences were analyzed using t-tests and diagnostic performance was assessed using receiver operating characteristic (ROC) curve analysis. Results: The mean CFCSA was significantly lower in the CFBS group (25.65 ± 7.19 mm²) compared to the control group (43.00 ± 8.38 mm²; p < 0.001). ROC analysis identified a CFCSA threshold of 33.02 mm² as the optimal cut-off point for predicting CFBS, yielding a sensitivity of 86.4%, a specificity of 86.7%, and an area under the curve (AUC) of 0.94 (95% CI: 0.91-0.96). Conclusions: These findings suggest that CFCSA is a robust and reproducible morphological parameter for evaluating foraminal stenosis. The proposed cut-off may enhance diagnostic accuracy and aid in clinical decision-making for patients presenting with C6 radiculopathy. However, given this study's retrospective, single-center design, further validation through multicenter, prospective studies across multiple cervical levels is warranted.

Background: This study aimed to evaluate whether low-concentration iodine contrast-enhanced multiphase low-monoenergetic computed tomography (LCLM CT; 270 mg I/mL, 40 keV) is non-inferior to standard-dose computed tomography (SDCT; 350 mg I/mL) in image quality and lesion detectability for chronic liver disease patients.

Methods: Sixty-seven patients underwent both protocols. Image quality was assessed using a 5-point scale with a non-inferiority margin of -0.5. Quantitative metrics included signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Lesion detectability was evaluated using jackknife free-response receiver operating characteristic (JAFROC) analysis with a -0.1 margin.

Results: LCLM CT reduced iodine dose per kilogram by 21.9%. Despite higher image noise, it achieved higher CNR for the aorta and hepatic lesions, as well as superior hepatic artery clarity. Image quality was non-inferior (difference: -0.119; 95% CI: -0.192 to -0.047), and lesion detectability (FOM: 0.744 vs. 0.721; difference: 0.023; 95% CI: -0.170 to 0.218) also showed non-inferiority.

Conclusions: LCLM CT maintains diagnostic performance and improves vascular contrast while reducing iodine burden, supporting its clinical utility in longitudinal HCC surveillance.