Purpose: This study evaluated the differences between arachnoid and epidermoid cysts in computerized tomography (CT) texture analysis (TA). Material and methods: The study included 12 patients with intracranial epidermoid cysts and 26 patients with intracranial arachnoid cysts who were diagnosed with diffusion-weighted magnetic resonance imaging (DW-MRI) and who had undergone an unenhanced CT examination before treatment. The LIFEx application software was used to obtain texture features. Eighty-two texture features from 38 lesions were automatically calculated for each lesion. The Shapiro-Wilk test was used to test the normality of the scores, and the Mann-Whitney U Test was used to test the difference between the groups. Receiver operating characteristic (ROC) curves and multivariate logistic regression modeling examined the parameters' diagnostic performances. Results: The median age of the patients was 53 years (range: 19-88 years). Eighty-two texture parameters were evaluated in the first order: gray-level co-occurrence matrix (GLCM), gray-level run length matrix (GLRLM), neighbor gray-tone difference matrix (NGTDM), and gray-level size zone matrix (GLSZM) groups. There was a statistically significant difference between the arachnoid cyst and the epidermoid cyst in the variables of compacity, compactness 1, compactness 2, sphericity, asphericity, sum average, coarseness, and low gray-level zone (p<0.05). According to the multiple logistic regression model, it was determined that the sum average in the GLCM group (B=-0.11; p=0.015), coarseness (B= 869.5; p=0.044) in the NGTDM group, and morphological sphericity (B=24.18; p=0.047) were the radiomics variables that increased the probability of epidermoid diagnosis. According to the classification table of the model, the sensitivity rate was found to be 83%, and the specificity rate was found to be 96%. Therefore, the probability of accurate model classification was 92%. Conclusion: CT TA is a method that can be applied with high diagnostic accuracy in the differential diagnosis of intracranial epidermoid and arachnoid cysts, especially in patients who cannot undergo an MRI examination.

Objective: The primary objective of our study was to evaluate the predictive performance of serum inflammatory markers and the semi-quantitative computed tomography severity scoring system on diagnosing the Covid 2019 disease and its course. Methods: Our study is a single-center retrospective cohort study. The data of 213 adults who were confirmed to have coronavirus disease 2019 by polymerase chain reaction tests in the period between April 2020 and August 2020 were evaluated. One hundred eighty four of these patients whose C-reactive protein, d-dimer, and ferritin levels, lymphocyte counts, and thoracic computed tomography images were obtained at the time of admission were included in the study. The semi-quantitative computed tomography severity score was calculated for all patients. Results: The median age of the 184 patients included in the study was 51.5 (19-91) years. The incidence of intensive care need and mortality was 10.3% (n = 19) and 5.4% (n = 10), respectively. The intensive care need and mortality rate was significantly correlated with higher thoracic computed tomography involvement scores at admission. There was a statistically significant and positive correlation between the computed tomography scores and the C-reactive protein, d-dimer, and ferritin levels. Older age (> 65 years-old) and thoracic computed tomography scores of 11 and higher were independent factors correlated with need for intensive care. Conclusion: Serum inflammatory markers and semi-quantitative computed tomography severity scoring system were predictive in diagnosing the Covid 2019 disease and its course.

Aim: Brain metastases are seen in 15–40% of patients diagnosed with cancer. We aimed to search the relationship between the T2 hypointensity, diffusion-weighted imaging characteristics, and the presence and amount of vasogenic edema of brain metastasis in magnetic resonance imaging (MRI). Methods: A total of 292 patients with brain metastasis were included in the study. T2 signals of metastatic lesions, accompanying diffusion restriction and perilesional vasogenic edema findings, were investigated. In metastases accompanied by vasogenic edema, the largest dimension of the vasogenic edema-mass complex on T2-weighted sequences and the largest dimension of the mass in contrast-enhanced T1-weighted series were measured and the edema-mass ratio (EMR) was calculated by comparing these two values. Results: The frequency of vasogenic edema was statistically significantly higher in T2 hypointense metastases (89.1% vs 58.8%, χ2 = 18.949, p = <.001) and metastases accompanied by diffusion restriction(81% vs 61.5%, χ2 = 6.971, p = .008). EMR values were found to be statistically significantly higher in T2 hypointense metastases (EMR→ Z = −4.507, p = <.001) and metastases with diffusion restriction(EMR→ Z = −3.819, p = .001). Conclusions: The frequency of vasogenic edema and EMR rates were higher in patients in T2 hypointense metastases and metastases accompanied by diffusion restriction in MRI.

Objective: This study aims to present a rare case of spontaneous intracystic hemorrhage accompanied by subdural hematoma in a patient with an arachnoid cyst. Such complications can lead to increased intracranial pressure, neurological deficits, and herniation if left untreated. Case Presentation: A 35-year-old female with a known arachnoid cyst in the left frontotemporal region, but no history of trauma, presented with severe left-sided headache. Contrast-enhanced brain magnetic resonance imaging (MRI) revealed hemorrhagic layering within the arachnoid cyst and a late subacute subdural hematoma with a thickness of up to 2 cm, exhibiting hyperintense signals on T1-weighted and T2-weighted/FLAIR sequences. The hematoma was associated with subfalcine herniation. Computed tomography (CT) angiography showed no vascular abnormalities apart from increased vascularity near the hematoma. The patient was managed conservatively, and follow-up MRI at one week confirmed hematoma stability. Conclusion: Spontaneous intracystic and subdural hemorrhages associated with arachnoid cysts are exceedingly rare and can occur without a history of trauma. This case highlights the importance of considering these complications in patients presenting with severe headaches and known arachnoid cysts. Radiological imaging should be planned for patients diagnosed with arachnoid cyst, especially those who present with headache complaints, even if they do not have a history of trauma. Early imaging with MRI and CT is crucial for diagnosis and management planning.

Background/Aim: The differential diagnosis of solitary brain tumors poses challenges for clinicians and radiologists, often leading to invasive biopsy procedures. Therefore, this study aimed to evaluate the variations in edema volume and diffusion characteristics between the tumor core and peritumoral zone in cases of glioblastoma, brain metastasis, and central nervous system lymphoma. The aim was to identify additional parameters for conventional magnetic resonance imaging (MRI) that could aid in the differential diagnosis. Methods: A total of 39 patients (13 with central nervous system lymphoma, 13 with glioblastoma, and 13 with brain metastases) were included in this retrospective cohort study. Apparent diffusion coefficient (ADC) values were calculated from the ADC maps obtained from Brain MRI for both the lesion and peritumoral region. Additionally, the largest diameter of the vasogenic edema-mass complex was measured using T2 sequences. In the contrast-enhanced series, the largest diameter of the metastatic lesion was measured. The edema-mass ratio was determined by dividing the diameter of the edema-mass complex by the diameter of the mass. Results: There was a statistically significant difference in the edema-mass ratio among the tumor types (P=0.008). Further analysis using Bonferroni correction revealed that this difference was primarily due to glioblastoma. Compared to patients with lymphoma and brain metastases, lesions diagnosed as glioblastoma exhibited a lower edema-mass ratio. Additionally, a statistically significant difference was observed in the ADC value measured from the lesion according to the tumor type (P=0.017). It was determined that lesions associated with central nervous system lymphoma had lower ADC values than those with glioblastoma. Conclusion: Including lesional and perilesional ADC values obtained through diffusion-weighted examination and edema mass ratio measurements may enhance the accuracy of differential diagnosis. Utilizing these imaging characteristics in a multiparametric approach, as suggested by this research, can improve the accuracy of diagnosing malignant cancers, thereby enabling better patient management and treatment decisions.

BACKGROUND: The etiology, clinicopathological features, and prognosis of cancer in cases with EGFR mutations are different from those without mutations. OBJECTİVE: This study aims to evaluate the differences in ADC histogram analysis in brain metastases with EGFR mutation status in lung adenocarcinoma cases and the relationship between ADC histogram analysis differences and overall survival. METHODS: In this retrospective case-control study, 30 patients (8 EGFR+/22 EGFR-) and 51 brain metastases (15 EGFR+/36 EGFR-) were included. ROI markings are first performed from each section, including metastasis in ADC mapping using FIREVOXEL software. Next, ADC histogram parameters are calculated. Overall survival analysis after brain metastasis (OSBM) is defined as the time from initial brain metastasis diagnosis to the time of death or last follow-up. Patient-based (by evaluating the largest lesion) and lesion-based (by evaluating all measurable lesions) statistical analyses are then performed. RESULTS: In the lesion-based analysis, skewness values are lower in EGFR+ patients, which is statistically significant (p = 0.012). The two groups have no significant difference regarding other ADC histogram analysis parameters, mortality, and overall survival (p > 0.05). In the ROC analysis, the most appropriate skewness cut-off value is determined as 0.321 to distinguish the EGFR mutation difference, and this value is statistically significant (sensitivity: 66.7%, specificity: 80.6%, AUC: 0.730) (p = 0.006). CONCLUSİON: The findings of this study provide valuable insights into the differences in ADC histogram analysis according to EGFR mutation status in brain metastases due to lung adenocarcinoma. The identified parameters, especially skewness, are potentially non-invasive biomarkers for predicting mutation status. Incorporating these biomarkers into routine clinical practice may aid treatment decision-making and prognostic assessment for patients. Further validation studies and prospective investigations are warranted to confirm the clinical utility of these findings and establish their potential for personalized therapeutic strategies and patient outcomes.