Radiologia Medica最新文献

Various imaging modalities play key roles throughout the different stages of prostate cancer. Each imaging modality has different strengths and weaknesses and various scoring systems or frameworks are used to interpret their findings. Discordances between imaging modalities or interpretation frameworks, and even with clinicopathological findings are not uncommon. Discordances often lead to challenges in the decision-making process, especially with dynamically changing indications for newer imaging modalities. While more research is needed on harmonizing interpretations across different modalities, multidisciplinary team discussion is key to optimizing management of patients with prostate cancer when such discordances are present. In this comprehensive review, we take a deep dive in to these various discordances seen in clinical practice and explore their clinical implications.

Purpose: This study aimed to develop and validate a prognostic model for hepatocellular carcinoma (HCC) patients undergoing liver resection, using the functional liver imaging score (FLIS) derived from hepatobiliary-specific contrast-enhanced magnetic resonance imaging (MRI).

Material and methods: A total of 694 pathologically confirmed HCC patients who underwent hepatobiliary-specific MRI with either gadoxetic acid or gadobenate dimeglumine and subsequent liver resection were included. FLIS was calculated by assigning 0-2 points to three hepatobiliary-phase MRI features: hepatic enhancement, biliary excretion, and portal vein signal intensity. Multivariable Cox regression identified AFP level, tumor size, and extent of resection as independent predictors of overall survival (OS).

Results: FLIS ≤ 2, alpha-fetoprotein (AFP) > 400 ng/mL, tumor size > 5 cm, and major resection were identified as independent predictors of worse OS. A predictive model combining these factors demonstrated excellent prognostic performance, with Harrell's concordance indices of 0.91 in the training cohort and 0.96 internal validation cohort, and 0.94 in external validation cohort. The FLIS-based model significantly outperformed FLIS alone and conventional clinical models (p < 0.05). Kaplan-Meier survival analysis showed that low-risk patients had significantly better OS and recurrence-free survival (RFS) compared to high-risk patients across all cohorts (p < 0.05).

Conclusion: FLIS is a simple, non-invasive imaging biomarker for evaluating liver function and predicting outcomes in HCC patients. When integrated with key clinical variables, the FLIS-based model demonstrates excellent discrimination and calibration for OS and RFS, providing accurate postoperative prognostic stratification and showing great potential for guiding surveillance and improving long-term survival outcomes in future clinical applications.

Purpose: This study sought to investigate the presence of residual myocardial hyperemia on the recovery phase in patients undergoing stress CMR.

Material and methods: Fifty patients with clinical indication for stress CMR underwent quantitative perfusion imaging in resting conditions, after regadenoson-induced hyperemia (400 mcg, 5 mL), and 10 min after recovery with euphylline. Studies showing hypoperfusion due to ischemia and/or prior myocardial infarction were excluded. Global myocardial blood flow during rest (MBF_rest), stress (MBF_stress) and recovery (MBF_recovery) and MPR indices (MPR_stress/rest and MPR_{stress/recovery}) were calculated using automated pixel-wise quantitative myocardial perfusion mapping.

Results: A total of 30 patients (22 males, mean age of 62.7 ± 1 years) were included in the analysis. Global MBF_rest and MBF_stress were 0.83 ± 0.2 mL/g/min and 2.1 ± 0.6 mL/g/min, respectively. After recovery with euphylline, myocardial perfusion did not return to the resting values (MBF_recovery of 0.92 ± 0.3 mL/g/min) and statistically differed from MBF_rest (p < 0.01), suggesting residual myocardial hyperemia. This resulted in an abnormally low MPR_{stress/recovery} (2.43 ± 0.7) with respect to MPR_stress/rest (2.56 ± 0.7) (p = 0.03). A linear mixed-effects model accounting for repeated measures revealed statistically significant group differences over time in global MBF (mean difference 0.1, 95% CI 0.02-0.17, p = 0.01) and global MPR (mean difference -0.13, 95% CI -0.25 to -0.02, p = 0.02).

Conclusion: Despite the use of euphylline to counteract the vasodilator effect, MBF does not completely revert to resting values and MBF_recovery cannot be used as a substitute for MBF_rest when regadenoson is used. Consequently, a rest/stress protocol is advised for quantitative CMR perfusion to obtain accurate MBF and MPR parameters.

Purpose: To differentiate interstitial lung diseases (ILDs) with fibrotic and inflammatory patterns using high-resolution computed tomography (HRCT) and a radiomics-based artificial intelligence (AI) pipeline.

Materials and methods: This single-center study included 84 patients: 50 with idiopathic pulmonary fibrosis (IPF)-representative of fibrotic pattern-and 34 with cellular non-specific interstitial pneumonia (NSIP) secondary to connective tissue disease (CTD)-as an example of mostly inflammatory pattern. For a secondary objective, we analyzed 50 additional patients with COVID-19 pneumonia. We performed semi-automatic segmentation of ILD regions using a deep learning model followed by manual review. From each segmented region, 103 radiomic features were extracted. Classification was performed using an XGBoost model with 1000 bootstrap repetitions and SHapley Additive exPlanations (SHAP) were applied to identify the most predictive features.

Results: The model accurately distinguished a fibrotic ILD pattern from an inflammatory ILD one, achieving an average test set accuracy of 0.91 and AUROC of 0.98. The classification was driven by radiomic features capturing differences in lung morphology, intensity distribution, and textural heterogeneity between the two disease patterns. In differentiating cellular NSIP from COVID-19, the model achieved an average accuracy of 0.89. Inflammatory ILDs exhibited more uniform imaging patterns compared to the greater variability typically observed in viral pneumonia.

Conclusion: Radiomics combined with explainable AI offers promising diagnostic support in distinguishing fibrotic from inflammatory ILD patterns and differentiating inflammatory ILDs from viral pneumonias. This approach could enhance diagnostic precision and provide quantitative support for personalized ILD management.

Purpose: This study aims to compare palliative cTACE, DEB-TACE and DSM-TACE in patients affected by HCC in intermediate BCLC stage in terms of efficacy and patient tolerance.

Materials and methods: Patients treated with palliative TACE were prospectively enrolled in two centers during 9 months. Procedures were performed superselectively in all patients. Inclusion criteria were: HCC diagnosis, intermediate BCLC stage, portal tree patency, preserved hepatic-renal-coagulation functions, palliative procedural aim, follow-up available up to 6-month post-TACE intervention. Exclusion criteria were: previous TACE treatments, alone or in combination with ablation in the same session, ascites, bilirubin > 2mg/dL, age < 18years, bridge to transplant procedural aim, concomitant infectious diseases. Primary endpoint was to compare efficacy and patients tolerance among the 3 different TACE techniques; secondary endpoint was to compare post-procedural complications occurrence.

Results: Seventy patients were included and divided into three groups according to the TACE technique: 24 were treated with cTACE, 25 with DEB-TACE, 21 with DSM-TACE. According to mRECIST criteria at 1-, 3- and 6-month follow-up, DEB-TACE presented better local response rates but without statistically significant differences. Patients treated with DSM-TACE showed significantly better tolerance, considering post-procedural transaminases and INR values together with clinical adverse events occurrence monitored up to 7 days. There were no differences in post-procedural complications and no major complications occurred.

Conclusions: In this study, in patients with intermediate-stage HCC undergoing palliative treatments, no significant differences emerged comparing cTACE, DEB-TACE and DSM-TACE in terms of procedural efficacy; however, patients treated with DSM-TACE showed significant better procedural tolerance.

Cerebrovascular accident is a leading cause of death and disability. Early detection of cerebrovascular diseases is crucial for timely treatment. This study introduces a novel method for the simultaneous generation of color-coded arteriography, venography, and dynamic angiography derived from dynamic contrast-enhanced magnetic resonance angiography and computed tomography perfusion. By realigning source images into time series volume data, this approach enables the classification of five dynamic phases, allowing for the creation of detailed angiographic images and facilitating a comprehensive evaluation of cerebrovascular accidents in the emergency room. The method enables rapid assessment of ischemic strokes, improving patient selection for recanalization therapy, and aids in the early diagnosis of other cerebrovascular diseases, including cerebral venous thrombosis and arteriovenous shunts. We demonstrate the clinical applications of this technique, highlighting its potential to enhance the accuracy and speed of cerebrovascular imaging, making it a valuable first-line diagnostic tool for stroke patients.

Recent advances in molecular genetics have revolutionized the classification of pediatric-type high-grade gliomas in the 2021 World Health Organization central nervous system tumor classification. This narrative review synthesizes current evidence on the following four tumor types: diffuse midline glioma, H3 K27-altered; diffuse hemispheric glioma, H3 G34-mutant; diffuse pediatric-type high-grade glioma, H3-wildtype and IDH-wildtype; and infant-type hemispheric glioma. We conducted a comprehensive literature search for articles published through January 2025. For each tumor type, we analyze characteristic clinical presentations, molecular alterations, conventional and advanced magnetic resonance imaging features, radiological-molecular correlations, and current therapeutic approaches. Emerging radiogenomic approaches utilizing artificial intelligence, including radiomics and deep learning, show promise in identifying imaging biomarkers that correlate with molecular features. This review highlights the importance of integrating radiological and molecular data for accurate diagnosis and treatment planning, while acknowledging limitations in current methodologies and the need for prospective validation in larger cohorts. Understanding these correlations is crucial for advancing personalized treatment strategies for these challenging tumors.

Purpose: Management of colorectal cancer (CRC) is determined by the stage of the disease and molecular features, such as microsatellite instability (MSI). MSI-high/deficient mismatch repair (MSI-H/dMMR) tumors respond better to immunotherapy but poorly to 5-FU-based treatments. With increasing use of neoadjuvant chemotherapy there is interest in developing non-invasive, radiomics models based on preoperative contrast-enhanced CT scans to predict MSI status and support personalized therapy.

Material and methods: Adult patients diagnosed with CRC who underwent pre-treatment staging with contrast-enhanced CT and had known MSI status were retrospectively analyzed. Portal venous phase images were assessed. Two radiologists, blinded to MSI status, manually segmented tumor regions on CT images. Radiomic features and statistical modeling were used to develop a predictive model for identifying the MSI-H phenotype.

Results: Analysis was conducted on 54 adult CRC patients who had undergone staging CT scans with known MSI status. Two different models were built considering different brands of CT machines. Twenty statistically significant radiomic features from the portal venous phase of CT images able to differentiate MSI from microsatellite stable (MSS) patients were selected for each model. LASSO regression was applied, selecting features for model construction. The best model's performance demonstrated an area under the ROC curve of 0.844 (95% CI = 0.73-0.96 DeLong, p < 0,05).

Conclusion: The results demonstrate the potential of the radiomics model as a non-invasive, cost-effective tool for MSI evaluation, guiding CRC therapy. It aids in identifying patients who would benefit from immunotherapy or chemotherapy, supporting the therapeutic shift from postoperative to preoperative treatment.

Metastatic involvement (MB) of the breast from extramammary malignancies is rare, with an incidence of 0.09-1.3% of all breast malignancies. Due to its variable clinical and radiological presentation, MB often mimics primary breast cancer (BC), leading to potential misdiagnosis and impacting treatment decisions. This narrative review analysed MB cases based on dissemination pathways: hematogenous (HM), lymphatic (LM), or direct contiguous (DC) spread. HM was the most frequent, particularly in melanoma, lung, renal, and gastrointestinal carcinomas, presenting as well-circumscribed, non-calcified nodules without axillary lymph node involvement, distinguishing them from BC. LM spread, common in HM malignancies, caused diffuse breast oedema, skin thickening, and a "peau d'orange" appearance, resembling inflammatory BC. DC spread, though rarer, was observed in advanced lung cancer, with infiltrative lesions extending from the chest wall. Multimodal imaging (Mammography (DM), Ultrasound (US), Magnetic Resonance Imaging (MRI), Computer Tomography (CT), and Positron Emission Tomography (PET)) was critical for detecting MB, while histopathological and immunohistochemical analysis confirmed extramammary origin. Due to the rarity and heterogeneity of MB, diagnosis requires a multidisciplinary approach integrating oncological history, imaging, and pathology. Recognising distinct imaging patterns can aid early diagnosis, avoid unnecessary surgery, and guide appropriate systemic therapy based on the primary malignancy. Early identification of the metastatic pattern may influence clinical management decisions and improve patient outcomes.

The male breast is predisposed to be affected by many of the same pathological processes as the female breast is. The diagnosis of male breast pathologies is generally achievable when clinical evaluation is combined with standard breast imaging methods such as mammography and ultrasound. Magnetic resonance imaging is also a valuable tool in diagnosing the main pathologies affecting the male breast, especially for evaluating pre- and post-surgical treatments and follow-up. However, although this technique has been sufficiently regulated and adopted by many breast radiologists for female breast imaging, its application in the diagnosis of male breast pathologies remains limited to a few specialized centers. This article, based on a retrospective analysis of the experience of the University of Verona, explores various aspects of male breast diseases, including benign conditions such as gynecomastia and breast implant ruptures in transgender women as well as malignant entities such as male breast cancer. Emphasis is placed on the distinctive morphological features, enhancement patterns and kinetics observed in male breast lesions on dynamic contrast-enhanced MRI. This article provides a comprehensive overview of the application of MRI in male breast disease assessment, highlighting the potential role of MRI as a complementary tool to traditional breast imaging techniques.