Polish journal of radiology最新文献

Brucellosis is a zoonotic disease caused by Gram-negative bacteria of the Brucella genus that can be acquired through contact with a contaminated animal or its secretions. The course of the disease can be acute, chronic, or persistent. Axial skeleton and central nervous system (CNS) are among the most common affected locations and may be involved in each of the forms. Due to the varying clinical picture of the disease, diagnosis is made mainly on the basis of laboratory examinations that detect specific IgM and IgG antibodies in blood or other biological material and/or cultures. Imaging methods, especially magnetic resonance imaging, can aid in establishing proper diagnosis, monitoring of the disease and, to some extent, enable differential diagnosis before obtaining the laboratory tests results. The aim of this review is to present imaging features of Brucella infection of the spine and CNS and provide the recent advancements in the field.

Purpose: To compare the image quality in single-pass split-bolus abdominal computed tomography (CT) and conventional biphasic CT in abdominal trauma patients.

Material and methods: Sixty-six consecutive abdominal trauma patients referred for CT were randomised into 2 groups: the study group (n = 33), scanned using the split-bolus technique; and the control group (n = 33), scanned using the conventional biphasic technique. CT image quality was analysed subjectively by 2 observers based on a 5-point Likert scale. The images were also analysed quantitatively for attenuation values achieved by region of interest (ROI) placements in major arteries, veins, and solid organs. In addition, the radiation dose in terms of the dose length product (DLP) was compared between the 2 groups.

Results: The image quality in both groups ranged from good to excellent in most cases. There was no statistically significant difference in subjective image quality in both the groups as assessed by Likert score. Attenuation values in solid organs and major venous structures were significantly higher in the split-bolus group (p < 0.001). Arterial attenuation values were significantly higher in the control group (p < 0.001), but diagnostic levels were achieved in all patients. There was a reduction of 31.1% in DLP in the split-bolus group.

Conclusions: The split-bolus technique offers comparable image quality and higher solid organ and venous enhancement than conventional biphasic protocol at a reduced radiation dose.

Purpose: To evaluate the performance of a combined clinical-radiomics model using multiple machine learning approaches for predicting pathological differentiation in hepatocellular carcinoma (HCC).

Material and methods: A total of 196 patients with pathologically confirmed HCC, who underwent preoperative computed tomography (CT) were retrospectively enrolled (training: n = 156; validation: n = 40). The modelling process included the folowing: (1) clinical model construction through logistic regression analysis of risk factors; (2) radiomics model development by comparing 6 machine learning classifiers; and (3) integration of optimal clinical and radiomic features into a combined model. Model performance was assessed using the area under the curve (AUC), calibration curves, and decision curve analysis (DCA). A nomogram was constructed for clinical implementation.

Results: Two clinical risk factors (BMI and CA153) were identified as independent predictors of differentiated HCC. The clinical model showed moderate performance (AUC: training = 0.705, validation = 0.658). The radiomics model demonstrated improved prediction capability (AUC: training = 0.840, validation = 0.716). The combined model achieved the best performance in differentiating HCC pathological grades (AUC: training = 0.878, validation = 0.747).

Conclusions: The integration of CT radiomics features with clinical parameters through machine learning provides a promising non-invasive approach for predicting HCC pathological differentiation. This combined model could serve as a valuable tool for preoperative treatment planning.

Purpose: This study aimed to explore the diagnostic value of high-resolution magnetic resonance images and tumour markers in predicting lymph node metastasis of rectal cancer.

Material and methods: The clinical, imaging, and pathological data of patients with suspected rectal cancer were collected. The baseline data, and surgical and pathological characteristics were compared between the lymph node metastasis group and no metastasis group. Univariate and multivariate logistic regression were used to analyse the clinical and pathological factors, and preoperative magnetic resonance imaging (MRI) signs of extramural vascular invasion and rectal cancer lymph node metastasis. A nomogram model was established with statistically significant factors.

Results: 150 patients were included. Among them, 50 (33.3%) presented with vascular tumour thrombus, and 72 (48.0%) had lymph node metastasis. The detection of regional lymph nodes (DWI-LN) was an independent risk factor for lymph node metastasis. The area under curve of the nomogram model was 0.804.

Conclusion: Preoperative serum CA19.9, and the relationship between tumour and peritoneal reflection in preoperative MRI and DWI-LN have clinical value in predicting lymph node metastasis in patients with rectal cancer.

Purpose: This study investigates the relationship between diffusion-weighted imaging (DWI) and mean apparent diffusion coefficient (ADC) values in predicting the genetic and molecular features of gliomas. The goal is to enhance non-invasive diagnostic methods and support personalised treatment strategies by clarifying the association between imaging biomarkers and tumour genotypes.

Material and methods: A total of 91 glioma patients treated between August 2023 and March 2024 were included in the analysis. All patients underwent preoperative magnetic resonance imaging (MRI), including DWI, and had available histopathological and genetic test results. Clinical data, tumour characteristics, and genetic markers such as IDH1 mutation, MGMT promoter methylation, EGFR amplification, TERT pathogenic variant, and CDKN2A deletion were collected. Statistical analysis was performed to identify correlations between ADC values, MRI perfusion parameters, and genetic characteristics.

Results: Significant associations were found between lower ADC values and aggressive tumour features, including IDH1-wildtype, MGMT unmethylated status, TERT pathogenic variant, and EGFR amplification. Additionally, distinct ADC patterns were observed in gliomas with CDKN2A, TP53, and PTEN gene deletions. These findings were further supported by contrast enhancement and other MRI parameters, indicating their role in tumour characterisation.

Conclusions: DWI and ADC measurements demonstrate strong potential as non-invasive tools for predicting glioma genetics. These imaging biomarkers can aid in tumour characterisation and provide valuable insights for guiding personalised treatment strategies.

Purpose: This study aimed to determine whether the mediastinal lymph node/tumour ratio (NTR) of the standardised uptake value (SUV) predicts N2 involvement more accurately than node SUV in patients with non-small cell lung cancer (NSCLC).

Material and methods: We retrospectively analysed consecutive patients with lung cancer at clinical stages I-IVA. All patients underwent positron emission tomography-computed tomography (PET-CT), followed by mediastinal staging using endobronchial ultrasound and endoscopic ultrasound imaging, and curative-intent lung resection with systematic lymph node dissection. Pathological examination of the surgical specimen was performed for confirmation.

Results: The data from 774 patients were analysed. There was a significant correlation between the risk of false-negative PET results for N2 disease and both the SUV of the mediastinal nodes (p = 0.012) and NTR (p = 0.030). The NTR outperformed node SUV in predictive ability; the Akaike information criterion was 307.268 for NTR compared to 308.498 for node SUV. Three factors were significantly associated with the positive predictive value of PET: patient age (p = 0.021), female sex (p = 0.012), and adenocarcinoma histology (p = 0.036). There were no significant correlations between PET sensitivity, specificity, and negative predictive value (NPV), and age, sex, body mass index (BMI), tumour grade, lobar location, or histological type.

Conclusions: The NTR may be a useful tool for excluding N2 disease in NSCLC. PET sensitivity and NPV for detecting N2 disease are not influenced by age, sex, BMI, tumour grade, lobar location, or histological type.

Four cases of girls with metastases of soft tissue or bone sarcomas to the reproductive system or breasts are reported. Two patients had metastases to the breast from rhabdomyosarcoma (RMS) of the limbs, one had metastases to the ovary from RMS of the foot, and one had metastases to the uterine venous plexus from chondrosarcoma of the sacrum. In each case, the appearance of metastases was shown in various imaging methods: ultrasound, magnetic resonance imaging, and computed tomography. A thorough literature review confirmed that only a few cases of soft tissue and bone sarcoma metastasis to the locations of primary interest of this article in girls have been described, especially in the context of reproductive organs. Despite the rare occurrence of this type of metastases, the malignant tumours mentioned above should be considered when differentiating the source. These rare clinical situations are woven into a review of malignant neoplasms' metastases to the reproductive organs and breast.