To investigate the relationship between computerized tomography (CT) findings and the Ocular Trauma Score (OTS) in patients with open globe injury (OGI). This study included 123 individuals with OGI, examining injury characteristics, clinical symptoms, and CT scans for scleral irregularity, reduced globe volume, dislocated crystalline lens, aberrant vitreous density, chorioretinal thickening, and foreign body/air presence. The prognostic value of CT imaging in OGI was evaluated by assessing its relationship with OTS findings. The most common OTS category was stage 3, found in 71 eyes (57.7%). The prevalent CT findings included severe scleral irregularity or globe collapse (34.1%), dislocated crystalline lens (33.3%), and abnormal vitreous density (26.8%). Multivariate analysis revealed that severe scleral irregularity or globe collapse (Odds Ratio [OR] = 1.36, p = 0.006) and abnormal vitreous density (OR = 1.7, p < 0.001) were significantly associated with more advanced OTS stages (I or II), indicating more severe ocular trauma. The presence of three CT findings was associated with a higher likelihood of falling into OTS stages I or II (OR = 6.82, p = 0.001). Conversely, the absence of CT findings was associated with a decreased probability of having more severe OTS stages (OR = 0.05, p < 0.001). The study concludes that imaging findings are valuable for correlating with the severity of open globe injuries, highlighting the importance of CT in assessing ocular trauma.

Purpose: to investigate the effects of vessel geometry on steno-occlusive and dilatative common iliac artery (CIA) pathologies. Methods: this single-center, retrospective study included 100 participants, namely 60 participants with a unilateral, isolated CIA pathology who were divided into three pathology-based groups (a stenosis group, n = 20, an occlusion group, n = 20, and an aneurysm group, n = 20) and 40 participants without a CIA pathology (control group). All participants underwent abdominal and pelvic computed tomography angiography. The aortoiliac region of the participants was reconstructed into three-dimensional models. Elongation parameters (tortuosity index (TI) and absolute average curvature (AAC)) and bifurcation parameters (iliac take-off angle, iliac planarity angle, and bifurcation angle) were determined using an in-house-written piece of software. Demographic data, anthropometric data, cardiovascular risk factor data, and medical history data were obtained from participants’ electronic health records. The following statistical methods were used: one-way ANOVA, chi-square test, t-tests, Wilcoxon test, Kruskal–Wallis test, and multivariate linear regression. Results: in the occlusion group, both TI and AAC values were significantly higher on the contralateral side than on the ipsilateral side (both p < 0.001), whereas in the aneurysm group the AAC values were significantly higher on the ipsilateral side than on the contralateral side (p = 0.001). The ipsilateral and contralateral TI and AAC values of the iliac arteries were significantly higher in the aneurysm group than in the other three groups (all p < 0.001). Age significantly affected all of the elongation parameters except for the TI of the infrarenal aorta (all p < 0.010 except the TI of the infrarenal aorta). In addition, the AAC values for the iliac arteries were significantly associated with obesity (ipsilateral iliac artery, p = 0.045; contralateral iliac artery, p = 0.047). Aortic bifurcation parameters did not differ significantly either within each group (ipsilateral versus contralateral side) or between the individual groups. Conclusions: occlusions tend to develop in relatively straight iliac arteries, whereas unilateral, isolated CIA aneurysms are more likely to occur in elongated aortoiliac systems.

Background/Objectives: To evaluate the clinical utility and diagnostic performance of quantitative MRI parameters (T1, T2*, R2*, and ADC) in differentiating renal tumor subtypes and WHO grades, and to assess their potential role in non-invasive tumor characterization. Methods: This retrospective study included 82 patients with histopathologically confirmed renal tumors who underwent preoperative contrast-enhanced MRI between July 2019 and January 2024. Quantitative measurements were obtained from tumor regions and contralateral healthy renal cortex using standardized ROI-based analysis. Parameters included T2*, native and post-contrast T1, R2* (1/T2*), and ADC values. Interobserver agreement was assessed. A Random Forest model was used as a supplementary analytical tool. Results: The cohort included 82 patients (mean age: 59.3 years). Tumors were classified into multiple subtypes, with clear cell carcinoma being the most common (n = 46). High-grade tumors (WHO grades 3–4) demonstrated significantly lower ADC values (p = 0.029) and larger tumor size (p = 0.0017). Significant differences in T2*, R2*, and ADC values were observed across tumor subtypes (p < 0.05). Quantitative MRI parameters demonstrated moderate discriminatory performance, with ADC emerging as the most robust biomarker. The Random Forest model achieved an overall accuracy of 93.2%, primarily driven by ADC and post-contrast T1 values. Conclusions: Quantitative MRI parameters, particularly ADC, provide clinically meaningful non-invasive biomarkers for renal tumor characterization. Their combined interpretation, supported by contralateral renal cortex comparison, may enhance clinical decision-making. Further validation in larger cohorts is warranted.

Purpose: There may be difficulties in diagnosing musculoskeletal system tumors with Magnetic Resonance Imaging (MRI). Advanced MRI imaging techniques may contribute to noninvasive diagnosis.The aim of our study was to evaluate the performance of perfusion magnetic resonance imaging quantitative data in the differentiation of benign and malignant musculoskeletal tumors. Material and Methods: Thirty-six histologically proven patients were included in the study retrospectively. All patients underwent 1.5-T perfusion MRI (magnetic resonance imaging) with T1 mapping and diffusion MRI. Four quantitative and one semiquantitative parameter were obtained for each tumor using the Toft pharmacokinetic model. ADCmean and ADCmin values were calculated from apparent diffusion coefficient (ADC) maps. Results: Eighteen of 36 patients (50%) had malignant tumors, and 18 had benign tumors. There were 26 soft tissue tumors and 10 bone tissue tumors. Among malignant and benign tumors, the best performance was found in the Ktrans, Kep, Ve values. (p=0.011, p=0.013, p=0,035). Conclusion: Ktrans and Kep values, which are indicators of increased permeability in the tumor, are noninvasive parameters for determining the malignant character of the tumor. The 'Ve' value is an indicator of the extracellular volume of the tumor. Ktrans, Kep and Ve maps can also guide the biopsy.

A BSTRACT: Background: Otosclerosis is an osteodystrophy of the otic capsule that can result in progressive hearing loss. Computed tomography (CT) is an effective method for assessing otosclerosis. Previous investigations have focused on density measurements on a single cochlear slice; however, otosclerosis can affect the entire otic capsule. Objectives: The purpose of this study is to propose a new diagnostic method for otosclerosis by performing measurements on the whole pericochlear area, providing a diagnostic framework that better reflects the pathophysiology of the disease. Methods: Between March 2017 and October 2023, surgically proven otosclerosis patients with previously performed temporal CT investigations were collected. Volumetric annotation and isolation of the pericochlear area were performed on CT images using Myrian software. The gray-level co-occurrence matrix of annotated regions was computed in two-dimensional (2D) and 3D. Principal component analysis (PCA) is applied. All calculations are carried out in Matlab 2021b®. Results: The results show that histogram and texture-based features fail to differentiate the patient and control groups in both 2D and 3D. However, the application of the proposed patch-based extraction together with the use of PCA demonstrated that 99.99% of the data variability can be represented by the first two principal components. Consequently, the performance in terms of correct classification, selectivity, and specificity percentages is calculated as 98.61% ± 1.32%, 97.34% ± 3.47%, and 97.34% ± 2.32%, respectively. Conclusions: In this study, our findings demonstrate that with the proposed volumetric analysis, robust discrimination between affected patients and the control group was achieved.