Polish journal of radiology最新文献

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.

Purpose: The purpose of this study was to evaluate the use of the transthoracic ultrasonography (US) for pleural adhesions and pleural thickening and to quantify pleural effusion by standardised sonographic techniques and its comparison with thoracoscopic findings. An assessment of the association between pleural thickness and pleural nodularity with histopathological examination findings was also attempted.

Material and methods: Thirty-one patients with suspected chest pathologies were initially assessed by transthoracic US followed by videothoracospy. Findings observed were noted and appropriately analysed statistically.

Results: Transthoracic US is 100% sensitive and specific for detecting pleural septations in the presence of pleural effusion with 100% accuracy. Gliding sign is a highly sensitive and specific sign to detect the pleural septations in absence of pleural effusion. There was no significant association of thickness of pleural septation with the pleural malignancy.

Conclusions: Transthoracic US plays an important role in the quantification of pleural effusion, assessment of the pleura and pleural space for pleural adhesion, pleural thickening, and guiding trocar insertion.

Purpose: Our aim was to evaluate the diagnostic efficacy of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) parameters [D, D*, f, and apparent diffusion coefficient (ADC) values] in the detection and staging of liver fibrosis in patients with hepatitis B virus (HBV).

Material and methods: In this prospective study, a patient group of 64 consecutive patients (with a mean age of 43 years, 30 women and 34 men) with HBV, who scheduled liver biopsy, and a control group of 30 healthy individuals without liver disease underwent IVIM-DWI scan. A total of 94 IVIM-DWI examinations were analysed. IVIM-DWI parameters were measured in the right lobe of the liver. The IVIM-DWI parameters of the patient and control groups were compared by Mann-Whitney U test. The patient group was classified into subgroups according to fibrosis stage of histopathological results. Receiver operating characteristic (ROC) analysis was conducted to assess the sensitivity and specificity of each parameter for detection and staging fibrosis.

Results: D and ADC values were significantly lower in the patient group compared to the control group (p < 0.05), while D* values were significantly higher (p < 0.05). No significant difference was observed in f values between the 2 groups. D* had the highest diagnostic performance, with a sensitivity of 78.1% and specificity of 73.3%, with a cut-off value of 1.4 × 10^-3 mm²/s in the differentiation of fibrosis stages.

Conclusions: IVIM-DWI, particularly the D, D*, and ADC parameters, is an adjunctive non-invasive alternative to biopsy in the staging of HBV-related liver fibrosis, especially for the prediction of advanced fibrosis.

Purpose: This single-centre study includes a comparative analysis of the diagnostic performance of contrast-enhanced mammography (CEM) and automatic breast ultrasound (ABUS). The study involved 81 patients with focal breast lesions, who underwent ABUS, full-field digital mammography (FFDM), and CEM.

Material and methods: A total of 169 focal lesions were found in 81 patients, of which 110 lesions were histopathologically verified, 92 were malignant, 5 were B3 lesions, and 13 were benign. On CEM 19 additional lesions not visible on other imaging examinations were found, and as many as 36 new lesions were detected on ABUS. The number of lesions detected in patients with multiple lesions were 106 from 169 on ABUS, 65 on FFDM, and 88 on CEM. The highest correlation between the lesion's margin and its histopathological character was found in FFDM (p < 0.00), then ABUS (p = 0.038), and the lowest in CEM (p = 0.043). Compliance in determining the lesions' size comparing to histopathology as a gold standard was the highest for ABUS (p = 0.258) and lower for CEM (p = 0.012).

Results: The sensitivity of ABUS, FFDM, and CEM was, respectively: 80.43, 90.22, and 93.48; specificity: 27.78, 11.11, and 11.11; positive predictive value (PPV): 85.06, 83.84, and 84.31; negative predictive value (NPV): 21.74, 18.18, and 25; and accuracy: 71.82, 77.27, and 80. The sensitivity and accuracy of the combination of FFDM and ABUS were, respectively, 100 (p = 0.02) and 84.55 (AUC = 0.947) and for the combination of FFDM + CEM 93.48 (p = 0.25) and 79.09 (AUC = 0.855).

Conclusions: The study confirms that both ABUS and CEM may serve as a valuable complementary method for FFDM.

The aim of this paper is to present the currently used classification of split cord malformation. Split cord malformation (SCM) is a developmental defect arising during neurulation, resulting in abnormal neural tube development, with the formation of a division within the spinal cord and dural sac. The terms diastematomyelia and diplomyelia are used in the literature to describe this defect. In 1992, Pang proposed the term SCM to describe all dysraphic spinal cord defects and classified them into type I and type II, depending on the nature of the sagittal septum within the spinal canal and the presence or absence of a divided dural sac. SCM type I includes cases with a bony septum and a divided dural sac, while SCM type II includes cases without a divided dural sac but with a fibrous septum present. Depending on the type of defect, and the location and extent of the split, the condition is accompanied by neurological symptoms of varying localisation and severity. As symptoms may worsen with the child's growth, surgical intervention to remove the septum is usually necessary. In this article, the authors present the defect based on literature data, describe the current terminology regarding the defect and associated anomalies, and present a set of features that should be assessed to classify lesions.

Purpose: Despite the low incidence of COVID myocarditis, its influence on outcomes is substantial. The pivotal role of cardiac magnetic resonance (CMR) in diagnosing myocarditis is considered to be associated with disease prognosis. The primary objective of this study was to conduct a comparative analysis of myocardial injury patterns, CMR pathologic features, outcomes, and their correlation with CMR findings in COVID- and non-COVID-related myocarditis.

Material and methods: This historical cohort study involved 124 patients diagnosed with myocarditis (COVID-19 or non-COVID-19), who underwent CMR between 2018 and 2021. The COVID group consisted of 70 individuals with a definite history of COVID-19 infection within 4 weeks, and the non-COVID group comprised 54 individuals who had no prior exposure to the SARS-CoV-2 virus. All patients were monitored for one year to assess the incidence of major adverse cardiovascular events (MACE). Additionally, baseline and follow-up echocardiography data were obtained with a minimum 3-month interval.

Results: In comparison between two groups regarding to indices of CMR, left ventricular (LV) ejection fraction (p < 0.001), right ventricular (RV) ejection fraction (p < 0.001) were significantly lower in non-COVID group, and significant LV and RV systolic dysfunction were meaningfully lower in the COVID group. Extension of late gadolinium enhancement (LGE) was significantly greater in COVID group. Finally, the incidence of MACE and mean event-free survival did not have significant difference between two groups.

Conclusions: Although CMR findings differed between the 2 groups, there was no significant difference in the risk of MACE or survival during one-year follow-up. Notably, LV and RV dysfunction were more prevalent in the non-COVID group, while extension of LGE was greater in the COVID group.

Purpose: Ovarian cancer is the fifth fatal cancer among women. Positron emission tomography (PET), which offers detailed metabolic data, can be effectively used for early cancer screening. However, proper attenuation correction is essential for interpreting the data obtained by this imaging modality. Computed tomography (CT) imaging is commonly performed alongside PET imaging for attenuation correction. This approach may introduce some issues in spatial alignment and registration of the images obtained by the two modalities. This study aims to perform PET image attenuation correction by using generative adversarial networks (GANs), without additional CT imaging.

Material and methods: The PET/CT data from 55 ovarian cancer patients were used in this study. Three GAN architectures: Conditional GAN, Wasserstein GAN, and CycleGAN, were evaluated for attenuation correction. The statistical performance of each model was assessed by calculating the mean squared error (MSE) and mean absolute error (MAE). The radiological performance assessments of the models were performed by comparing the standardised uptake value and the Hounsfield unit values of the whole body and selected organs, in the synthetic and real PET and CT images.

Results: Based on the results, CycleGAN demonstrated effective attenuation correction and pseudo-CT generation, with high accuracy. The MAE and MSE for all images were 2.15 ± 0.34 and 3.14 ± 0.56, respectively. For CT reconstruction, such values were found to be 4.17 ± 0.96 and 5.66 ± 1.01, respectively.

Conclusions: The results showed the potential of deep learning in reducing radiation exposure and improving the quality of PET imaging. Further refinement and clinical validation are needed for full clinical applicability.

Purpose: To evaluate the diagnostic accuracy of different abbreviated magnetic resonance imaging (AMRI) protocols consisting of dynamic enhanced + T2-weighted imaging (T2W) and diffusion-weighted imaging (DWI) + T2W for the detection and characterization of liver metastases in a patient group with known colorectal cancer.

Material and methods: A total of 197 hepatic lesions were retrospectively analyzed across 3 different MRI sets: AMRI-1 (dynamic enhanced + T2W), AMRI-2 (DWI + T2W), and a standard MRI protocol. The patient cohort included 100 individuals (63 males, 37 females) with a mean age of 62.6 years (SD: 11.1 years). Lesions were characterized as benign, malignant, or indeterminate based on histopathology, positron emission tomography-computed tomography (PET-CT), and follow-up imaging.

Results: The standard MRI protocol identified 197 liver lesions (175 metastatic, 18 benign, and 4 indeterminate); 142 lesions (72.1%) were larger than 10 mm, with the majority being metastatic (140/142). Radiologist 1 identified 195 lesions using the AMRI-1 protocol (175 metastatic, 15 benign, and 5 indeterminate). The sensitivity per lesion was 89.7% (95% CI: 0.85-0.93). Radiologist 2 identified 183 lesions using the AMRI-2 protocol (169 metastatic, 6 benign, and 8 indeterminate). The sensitivity per lesion was 92.3% (95% CI: 0.88-0.95). No statistically significant difference was found in sensitivity between the AMRI-1 and AMRI-2 and standard MRI protocols (p > 0.05).

Conclusions: The standard MRI protocol demonstrated the highest sensitivity and specificity for detecting and characterizing liver metastases. However, differences between the protocols were not statistically significant. Abbreviated MRI protocols, particularly the AMRI-2 protocol incorporating diffusion-weighted imaging, could serve as an effective alternative for routine clinical practice.

Purpose: This study aimed to compare the findings of magnetic resonance imaging (MRI) and ¹⁸F-fluorodeoxyglucose (FDG)-positron emission tomography/computed tomography (PET/CT) to differentiate reactive lymphadenitis from nodal lymphoma of the head and neck.

Material and methods: This study included 138 patients with histopathologically confirmed cervical lymphadenopathy, including 35 patients with reactive lymphadenitis and 103 patients with nodal lymphoma, who had neck MRI (n = 63) and/or ¹⁸F-FDG-PET/CT (n = 123) before biopsy. The quantitative and qualitative MRI results and maximum standardised uptake value (SUV_max) were retrospectively analysed and compared between the 2 pathologies.

Results: The maximum diameter (22.4 ± 6.9 vs. 33.3 ± 16.0 mm, p < 0.01), minimum diameter (15.8 ± 3.6 vs. 22.3 ± 8.5 mm, p < 0.01), and SUV_max (6.9 ± 2.7 vs. 12.8 ± 8.0, p < 0.01) of the lesion were lower in reactive lymphadenitis than in nodal lymphoma, respectively. T2-hypointense-thickened capsules > 2 mm (46% vs. 14%, p < 0.05) and T2-hypointense areas converging to the periphery (15% vs. 0%, p < 0.05) were more frequently observed in reactive lymphadenitis than in nodal lymphoma, respectively. Hilum of nodes on T2-weighted images (54% vs. 22%, p < 0.05) and diffusion-weighted images (69% vs. 30%, p < 0.05) were more frequently demonstrated in reactive lymphadenitis than in nodal lymphoma, respectively.

Conclusions: Reactive lymphadenitis had a smaller size and lower SUV_max. The presence of T2-hypointense-thickened capsules, T2-hypointense areas converging to the periphery, and hilum of nodes were signs of reactive lymphadenitis.

Purpose: Early detection of breast cancer is crucial for improving patient outcomes. With advancements in artificial intelligence (AI), there is growing interest in its potential to assist radiologists in interpreting mammograms for early cancer detection. AI algorithms offer the promise of increased accuracy and efficiency in identifying subtle signs of breast cancer, potentially complementing the expertise of radiologists and enhancing the screening process for early-stage breast cancer detection.

Material and methods: A systematic literature review was conducted to identify and select original research reports on breast cancer diagnosis by artificial intelligence versus conventional radiologists in using mammograms in accordance with the PRISMA guidelines. Data were analysed with Review Manager version 5.4. P-value and I² were used to test the significance of differences.

Results: This systematic review and meta-analysis included 8 studies with data from a total of 120,950 patients. Regarding the sensitivity of AI, the pooled analysis of 6 studies with sensitivities ranging from 0.70 to 0.89 yielded a sensitivity of 0.85. However, the sensitivity of the radiologists ranged from 0.63 to 0.85, with an overall sensitivity of 0.77. As for specificity, both radiologists and AI groups had closer results.

Conclusions: The comparison between AI systems and radiologists in detecting early-stage breast cancer from mammograms highlights the potential of AI as a valuable tool in breast cancer screening. While AI algorithms have shown promising results in terms of accuracy and efficiency, they should be viewed as complementary to radiologists rather than replacements.