Polish journal of radiology最新文献

Purpose: This study aimed to assess the diagnostic performance of multiphase contrast-enhanced computed tomography (MCECT) in differentiating benign and malignant solid and cystic small renal masses (SRMs), predicting histologic subtypes, and grading, using signal intensity (SI) and tumour-to-cortex signal intensity (TCSI) ratio.

Material and methods: A retrospective analysis was conducted on 181 patients with solid and cystic SRMs (≤ 4 cm). MCECT imaging across 4 phases (non-contrast, corticomedullary, nephrographic, and excretory) was performed. SI and TCSI values were measured, and their diagnostic performance was evaluated using receiver operating characteristic (ROC) analysis. Solid, Bosniak IIF, III, and IV SRMs underwent histopathological confirmation.

Results: Among solid SRMs, excretory phase SI achieved an area under the curve (AUC) of 0.848 for differentiating RCC from other SRMs, with 100% sensitivity and 61.3% specificity. For distinguishing renal cell carcinoma (RCC) from benign SRMs, the most effective parameter was the TCSI ratio obtained from computed tomography excretory phase (88.6% sensitivity, 52.4% specificity, 0.763 AUC). For Bosniak IIF cysts, the corticomedullary phase SI provided an AUC of 0.902, with 93% sensitivity and 87.5% specificity. RCC subtyping showed distinct SI characteristics across phases, particularly for clear cell RCC. Nephrographic phase SI differentiated low- versus high-grade RCC, with an AUC of 0.901, 90.2% sensitivity, and 86.4% specificity.

Conclusions: MCECT-derived imaging biomarkers, particularly SI and TCSI, are effective non-invasive tools for characterising SRMs, aiding in the differentiation of benign and malignant lesions, histological subtypes, and tumour grades. Their integration with advanced radiomics could further enhance diagnostic accuracy.

Purpose: To analyse the risk and factors associated with false-negative (FN) and false-positive (FP) positron emission tomography-computed tomography (PET-CT) results in the mediastinal staging of non-small cell lung cancer.

Material and methods: This retrospective cohort study analysed data from a prospective database. It included patients with lung cancer who underwent preoperative staging with PET-CT, endobronchial ultrasound, and endoscopic ultrasound, followed by curative-intent anatomical lung resection with systematic lymph node dissection. Statistical analyses were performed to identify factors associated with FN and FP PET-CT results.

Results: Data from 781 patients were analysed. FN results were significantly associated with more advanced PET-CT-based stages and CT-based stage IIB. FP results were significantly associated with male sex, adenocarcinoma histology, CT-based disease stage, and SUV_max values of the primary tumour and lymph nodes.

Conclusions: False-negative PET-CT results in the diagnosis of mediastinal lymph node involvement were more likely to occur in PET-CT-based stages IB and IIB and less likely to occur in stage IIIA. FP results were more likely to be expected in men, with higher SUV_max values of the primary tumour and a more advanced CT-based stage of the disease.

Purpose: Endovascular procedures have become the method of choice for treating splenic artery aneurysms (SSAs). However, there is no consensus regarding the intervals and imaging methods for follow-up examinations in patients with true SAAs treated with coil embolisation. We aimed to evaluate the utility of digital subtraction angiography (DSA), computed tomography angiography (CTA), magnetic resonance angiography (MRA), contrast-enhanced ultrasound, and duplex ultrasound (DUS) for follow-up screening of patients with SAAs treated with coil embolisation.

Material and methods: We conducted a systematic review according to the PRISMA 2020 Statement. We searched 5 databases: Embase, Medline Ultimate, PubMed, Scopus, and Web of Science, each up to 10 April 2024. Eventually, 20 relevant original studies were included.

Results: DSA is an invasive procedure that requires ionising radiation and should not be performed as a routine check-up. CTA is an appropriate examination method in patients immediately after coil embolisation in whom severe complications, primarily bleeding, are suspected. Still, it is unsuitable for assessing persistent aneurysmal sac perfusion. MRA is a promising noninvasive technique that does not require ionising radiation. Several studies have demonstrated the superiority of MRA over DSA in detecting small aneurysmal sac reperfusion. DUS, while not a standalone method, may supplement MRA in patients at low risk of reintervention.

Conclusions: The evidence regarding follow-up imaging methods after SAAs coil embolisation is limited and of low quality. MRA should be preferred over DSA for detecting aneurysmal sac reperfusion. Due to artifacts, CTA is suitable for emergency cases but not for routine follow-up.

Purpose: To assess the influence of long- and short-segment spinal ankylosis on the characteristics and course of acute thoracolumbar fractures.

Material and methods: Computed tomography (CT) studies of 372 patients who were diagnosed with acute thoracolumbar spine fracture in our hospital between 2014 and 2020 were retrospectively reviewed. Demographic data, presence or absence of rigid spine conditions, location, and fracture morphology according to the Arbeitsgemeinschaft für Osteosynthesefragen (AO) spine classification were assessed. Statistical analysis was performed using the χ² test.

Results: A total of 65 patients with fractures through ankylosed segment or immediately adjacent segment (rigid spine group) and 307 controls were identified. Most rigid spine patients suffered minor trauma. In both groups most of the fractures were located in the thoracolumbar junction, and type A1 fractures were most common, followed by types A3 and A4. Multilevel fractures were more common in rigid spine patients (41.54% vs. 30.29%). Most of the rigid spine fractures (46.96%) were located within the fused spinal segment, with the midportion of the fused spinal segment being the most common location of types B and C fractures. Long-segment fusion was associated with unstable type B and C fractures. In short-segment fusion, single level type A fractures were most common. Spinal cord injury occurred only in patients with delayed diagnosis.

Conclusions: When plain films are used as a first-line diagnostic test for thoracolumbar spine trauma in stable patients without abnormal neurological signs or symptoms, and long-segment spinal ankylosis is observed, thoracolumbar CT should be used for further evaluation.

Purpose: This study compares breast carcinoma (BC) clinical tumour staging by contrast-enhanced mammography (CEM), full-field digital mammography (FFDM), and ultrasound (US). Clinical staging is essential for multidisciplinary teams to develop optimal treatment plans and for cancer registries to generate accurate analyses of cancer epidemiology.

Material and methods: Data on tumour size and the presence of multiplicity were extracted from radiology reports. Primary tumour staging (cT category) was established for each imaging modality. Enrolled cases (n = 78, adult females) had FFDM and US performed up to a month prior to CEM. Fisher's exact test was used to examine the relationship between cT stage determination and diagnostic methods.

Results: Tumour size was largest in CEM (median 47 mm), followed by FFDM (median 33 mm), and smallest in US (median 23 mm). There were statistically significant differences in the distribution of cT categories between the 3 imaging modalities, with cT2 and cT1 being most common in US (46% and 41%, respectively) and FFDM (53% and 19%, respectively). Staging by CEM followed a different pattern, with cT2 and cT3 being most common (both 38%). The multiplicity rate was equal for CEM and US (42%), with fewer cases in FFDM (13%).

Conclusions: The tumour size measured by CEM is greater compared to measurements obtained through US and FFDM. Given the strong correlation between CEM and histopathology reported in the literature, CEM enhances the accuracy of local tumour staging in BC, thereby minimising the risk of understaging.

Purpose: Synthetic magnetic resonance imaging (MRI) allows reconstruction of multiple contrast-weighted images from a single acquisition of multiple delay multiple echo (MDME) sequence with quantitative relaxometry (longitudinal relaxation rate [R1], transverse relaxation rate [R2], and proton density [PD]) in a shorter acquisition time. We tried to explore synthetic MR-based relaxometry to differentiate central nervous system (CNS) tuberculomas from primary CNS neoplasm like glioblastoma.

Material and methods: Ten cases of CNS tuberculoma and 14 cases of glioblastoma underwent pre- and post-contrast synthetic MRI. R1, R2, and PD values were calculated from lesion core, wall, and perilesional oedema using free-hand region of interest and compared across the 2 groups.

Results: Both pre- and post-contrast R1 and R2 relaxation rates from core were significantly higher in tuberculoma (mean pre-contrast R1 - 0.93, R2 - 15.02; post-contrast R1 - 1.51, R2 - 15.48) from glioblastoma (mean pre-contrast R1 - 0.36, R2 - 4.58; post-contrast R1 - 0.43, R2 - 4.78). The same values were higher in perilesional oedema of glioblastoma (mean pre-contrast R1 - 0.75, R2 - 9.9; post-contrast R1 - 0.78, R2 - 10.48) compared to tuberculoma (mean pre-contrast R1 - 0.68, R2 - 8.57; post-contrast R1 - 0.72, R2 - 8.67). No significant difference was seen between relaxometry parameters from the walls of lesions.

Conclusions: Synthetic MR-based relaxometry can be useful in distinguishing CNS tuberculomas from glioblastoma. R1 and R2 relaxation rates from core of the lesions are most important in differentiating the two with R1 value > 0.852 and R2 value > 11.565 from core strongly suggests tuberculoma over glioblastoma.

Purpose: Extracranial internal carotid artery dissections (EICAD) remain a relatively common cause of ischaemic events in young patients. Currently, there is no consensus on standardised use of endovascular therapy in the treatment of these patients, but available data suggest that conservative treatment is not sufficient in 15% of cases. The aim of our study was to evaluate if endovascular stent placement was safe and effective for the treatment of extracranial internal carotid artery dissection, and whether it should be considered in properly selected patients.

Material and methods: This single-centre, retrospective study aimed to evaluate procedural and clinical outcomes of patients with EICAD who underwent endovascular stenting between 2015 and 2024. Procedural and clinical efficacy and safety, the rate of complications, and long-term outcomes were noted.

Results: A total of 21 patients (10 females) with an average age of 53 years underwent stenting for EICAD. Technical success was achieved in all cases. Perioperative complications were noted in 2 cases. Neurological evaluation performed at 6-month follow-up showed very good clinical results in the majority of cases (mRS 0 and mRS 1 were 76% and 19%, respectively). Control imaging examinations confirmed stent patency in all cases. No long-term mortality was observed.

Conclusions: This retrospective study demonstrated procedural and clinical safety and efficacy of endovascular stenting in patients with extracranial internal carotid artery dissection. That is why endovascular therapy should be proposed to individuals with unsatisfactory response to medical treatment and in cases of disease progression.

Purpose: We aim to evaluate the reproducibility of these features and apply machine learning algorithms to predict cancer diagnosis.

Material and methods: We analyzed magnetic resonance (MR) images from a cohort of 82 individuals, split between 41 prostate cancer patients and 41 healthy controls. A total of 215 radiomic features were extracted from T2-weighted and ADC images using the Software Environment for Radiomic Analysis (SERA). Intraclass correlation coefficient (ICC) analysis was used to assess the reproducibility of features, and Pearson's correlation was applied to remove redundant features. After feature selection, seven dimensionality reduction techniques, including principal component analysis (PCA), kernel PCA, linear discriminant analysis, and locally linear embedding, were applied to preprocess the radiomic features. Ten machine learning algorithms, including support vector machines (SVM), random forests, neural networks, logistic regression, and ensemble methods such as CatBoost and AdaBoost, were utilized to classify cancerous versus non-cancerous tissues. Model performance was evaluated using accuracy and AUC-ROC metrics.

Results: The results showed that features with high reproducibility (ICC > 0.75) contributed significantly to the performance of machine learning models. SVM, neural networks, and logistic regression achieved the highest accuracy (0.88-0.9) and AUC (up to 0.93) when using features from the good and excellent reproducibility categories. PCA emerged as the most effective dimensionality reduction method, preserving the discriminative power of reproducible features across all models.

Conclusion: The results indicate that radiomic feature extraction from MR images, combined with dimensionality reduction and machine learning algorithms, provides a robust approach for prostate cancer diagnosis.

Purpose: This study aims to assess the accuracy of artificial intelligence (AI) in mandibular canal (MC) segmentation on cone-beam computed tomography (CBCT) compared to semi-automatic segmentation. The impact of third molar status (absent, erupted, impacted) on AI performance was also evaluated.

Material and methods: A total of 150 CBCT scans (300 MCs) were retrospectively analysed. Semi-automatic MC segmentation was performed by experts using Romexis software, serving as the reference standard. AI-based segmentation was conducted using Diagnocat, an AI-driven cloud-based platform. Three-dimensional segmentation accuracy was assessed by comparing AI and semi-automatic segmentations through surface-to-surface distance metrics in Cloud Compare software. Statistical analyses included the intraclass correlation coefficient (ICC) for inter- and intra-rater reliability, Kruskal-Wallis tests for group comparisons, and Mann-Whitney U tests for post-hoc analyses.

Results: The median deviation between AI and semi-automatic MC segmentation was 0.29 mm (SD: 0.25-0.37 mm), with 88% of cases within the clinically acceptable limit (≤ 0.50 mm). Inter-rater reliability for semi-automatic segmentation was 84.5%, while intra-rater reliability reached 95.5%. AI segmentation demonstrated the highest accuracy in scans without third molars (median deviation: 0.27 mm), followed by erupted third molars (0.28 mm) and impacted third molars (0.32 mm).

Conclusions: AI demonstrated high accuracy in MC segmentation, closely matching expert-guided semi-automatic segmentation. However, segmentation errors were more frequent in cases with impacted third molars, probably due to anatomical complexity. Further optimisation of AI models using diverse training datasets and multi-centre validation is recommended to enhance reliability in complex cases.