To systematically investigate the impact of image preprocessing parameters on the segmentation-based reproducibility of magnetic resonance imaging (MRI) radiomic features. The MRI scans of 50 patients were included from the multi-institutional Brain Tumor Segmentation 2021 public glioma dataset. Whole tumor volumes were manually segmented by two independent readers, with the participation of eight readers. Radiomic features were extracted from two sequences: T2-weighted (T2) and contrast-enhanced T1-weighted (T1ce). Two methods were considered for discretization: bin count (i.e., relative discretization) and bin width (i.e., absolute discretization). Ten discretization (five for each method) and five resampling parameters were varied while other parameters were fixed. The intraclass correlation coefficient (ICC) was used for reliability analysis based on two commonly used cut-off values (0.75 and 0.90). Image preprocessing parameters had a significant impact on the segmentation-based reproducibility of radiomic features. The bin width method yielded more reproducible features than the bin count method. In discretization experiments using the bin width on both sequences, according to the ICC cut-off values of 0.75 and 0.90, the rate of reproducible features ranged from 70% to 84% and from 35% to 57%, respectively, with an increasing percentage trend as parameter values decreased (from 84 to 5 for T2; 100 to 6 for T1ce). In the resampling experiments, these ranged from 53% to 74% and from 10% to 20%, respectively, with an increasing percentage trend from lower to higher parameter values (physical voxel size; from 1 x 1 x 1 to 2 x 2 x 2 mm³). The segmentation-based reproducibility of radiomic features appears to be substantially influenced by discretization and resampling parameters. Our findings indicate that the bin width method should be used for discretization and lower bin width and higher resampling values should be used to allow more reproducible features.

Adherence to the Checklist for Artificial Intelligence in Medical Imaging (CLAIM): an umbrella review with a comprehensive two-level analysis - Diagnostic and Interventional Radiology

Purpose: To assess whether diffusion tensor imaging (DTI) and generalized q-sampling imaging (GQI) metrics could preoperatively predict the clinical outcome of deep brain stimulation (DBS) in patients with Parkinson’s disease (PD). Methods: In this single-center retrospective study, from September 2021 to March 2023, preoperative DTI and GQI examinations of 44 patients who underwent DBS surgery, were analyzed. To evaluate motor functions, the Unified Parkinson’s Disease Rating Scale (UPDRS) during on- and off-medication and Parkinson’s Disease Questionnaire-39 (PDQ-39) scales were used before and three months after DBS surgery. The study population was divided into two groups according to the improvement rate of scales: ≥ 50% and < 50%. Five target regions, reported to be affected in PD, were investigated. The parameters having statistically significant difference were subjected to a receiver operating characteristic (ROC) analysis. Results: Quantitative anisotropy (qa) values from globus pallidus externus, globus pallidus internus (qa_Gpi), and substantia nigra exhibited significant distributional difference between groups in terms of the improvement rate of UPDRS-3 scale during on-medication (p = 0.003, p = 0.0003, and p = 0.0008, respectively). In ROC analysis, the best parameter in predicting DBS response included qa_Gpi with a cut-off value of 0.01370 achieved an area under the ROC curve, accuracy, sensitivity, and specificity of 0.810, 73%, 62.5%, and 85%, respectively. Optimal cut-off values of ≥ 0.01864 and ≤ 0.01162 yielded a sensitivity and specificity of 100%, respectively. Conclusion: The imaging parameters acquired from GQI, particularly qa_Gpi, may have the ability to non-invasively predict the clinical outcome of DBS surgery.

Objective: The present study aimed to evaluate the clinical success of computed tomography (CT)–guided radiofrequency ablation (RFA) in the treatment of proximal femoral located intra-articular osteoid osteoma (IAOO). Methods: This retrospective study included consecutive patients with clinical and CT imaging features suggestive of IAOO who were treated using a standardized CT-guided RFA technique between January 2020 and September 2024. The clinical, demographic, and radiological characteristics of the patients were documented. The efficacy and results of the RFA treatment were evaluated. Results: Based on the inclusion criteria, 20 patients were included in the study. The mean follow-up period was 29.2 months (range: 6-48 months). The median procedure time was 43 minutes. No immediate or late major or minor complications were recorded. Technical success was achieved in 100% of the cases. In 3 of 20 patients, pain symptoms recurred within the first month, so RFA was performed again, and full clinical success was achieved. The preoperative mean Visual Analogue Scale (VAS) score was 7.4 (range: 5-10). The postoperative first month mean VAS score was 1.2 (range: 0-2). Conclusion: Computed tomography–guided RFA is a highly safe and effective technique that can be considered as the first choice for treating symptoms associated with proximal femoral IAOO. Performing all manipulations under CT guidance at all stages of the procedure, accessing the nidus through extra-articular normal bone, and centralizing the nidus with the RFA probe facilitates the safety of the technique and prevents damage to the articular cartilage. Level of Evidence: Level IV, Therapeutic StudyCite this article as: Çakır MS, Ercan CC, Karagülle M, Aycan OE, Polat B, Acunas B. Computed tomography–guided radiofrequency ablation in the treatment of intra-articular proximal femoral osteoid osteoma. Acta Orthop Traumatol Turc., 2025;59(5):292-298.

Objectives: Glioblastoma is the most common primary neoplasm of the central nervous system (CNS) and has a very poor prognosis. Ki-67 proliferative index is a value that reflects the mitotic index of the tumor and is associated with poor prognosis. The radiological features of the tumors can predict the course of the disease. The aim of this study is to evaluate the relationship between the morphology and the apparent diffusion coefficient (ADC) values of the tumor with the Ki-67 index on preoperative magnetic resonance imaging (MRI). Methods: Preoperative MRI images of 52 patients with pathological diagnosis of glioblastoma were evaluated retrospectively. A score ranging from 1 to 3 was assigned to each of the morphological features of the tumors (peritumoral edema, necrosis, contrasting pattern, heterogeneity, hemorrhage, mass effect, tumor contour irregularity), and was added up to obtain the total score. In addition, the ADC values of each tumor were measured at the workstation. ADC value and total score of each tumor, and Ki-67 values obtained histopathologically were compared. Results: There was a negative correlation between Ki-67 index of tumors and ADC values (r=-0.895, p = 0.0001). A significant positive correlation was found between the morphological features of the tumors and their total scores (r=0.772, p = 0.0001). A statistically significant negative correlation was found between total score and ADC values (r=-0.780, p = 0.0001). Heterogeneity and necrosis were the features most closely associated with Ki-67. These were followed by mass effect, hemorrhage and contour irregularity, respectively. Conclusions: The morphological findings and ADC values obtained from preoperative MRI are related to the Ki-67 value, and thus can be used to predict prognosis and guide treatment in the early period.

Amyloid spherule-containing prolactinomas are rare entities associated with dopamine agonist (DA) resistance and aggressive behaviour. We report a giant amyloid spherule-containing prolactinoma with a substantial tumour burden and markedly elevated prolactin levels, highlighting novel multimodal therapeutic strategies. A 49-year-old man presented with headache and visual disturbance. Imaging revealed a giant pituitary macroadenoma (63 × 84 × 46 mm) with Knosp grade 4 cavernous sinus invasion and clivus erosion. Laboratory investigations revealed marked hyperprolactinemia (prolactin (PRL): 30,969 ng/mL) and autonomous growth hormone (GH) hypersecretion. Histopathology confirmed a sparsely granulated lactotroph tumour with extensive amyloid spherules and dystrophic calcifications (Ki-67: 8%). Notably, immunohistochemistry demonstrated PRL positivity without GH immunoreactivity, suggesting tumour heterogeneity with sampling limitations. Comprehensive systemic amyloidosis screening, the first systematic evaluation reported for this entity, excluded systemic disease. Following surgical debulking with extensive residual disease, postoperative cabergoline treatment resulted in a reduction in the PRL (4,700→927 ng/mL). Given the presence of amyloid-associated dopamine resistance, cabergoline was discontinued, and radiotherapy (RT) (45 Gy) was initiated to control the amyloid burden, followed by temozolomide. Based on evidence from other malignancies suggesting RT-mediated amyloid reduction, cabergoline was reintroduced postradiotherapy without paradoxical tumour growth. Concurrent cabergoline-temozolomide therapy, a novel approach that differs from conventional sequential protocols, achieved a dramatic response: 93.4% prolactin reduction (10,320→677 ng/mL) and 52.4% tumour volume reduction. This superior outcome far exceeded that of initial postsurgical cabergoline monotherapy (80% reduction), suggesting that RT successfully modulated the amyloid burden and restored dopamine sensitivity. This case suggests that RT may restore dopamine agonist sensitivity in patients with amyloid-containing prolactinomas, potentially enabling concurrent dopamine agonist-temozolomide therapy in refractory cases, warranting further validation.