Radiologia Medica最新文献

Objective: To explore the prognostic value of body compositions and radiomics in patients with resectable colon cancer, and to develop and validate a clinical-radiomics model for predicting the postoperative overall survival of patients with resectable colon cancer.

Methods: This study included 296 patients (43 months of median follow-up) with resectable colon cancer. Non-contrast CT images were used to quantify the body composition at the level of the third lumbar vertebra. Radiomics features were extracted from portal venous-phase CT scans. The recursive feature elimination and the least absolute shrinkage and selection operator regression were used for feature selection and construction of radiomic signatures. Univariate and multivariate Cox regression analysis were used to identify body composition. Combined with radiomics features, clinical-radiomics prediction model was constructed and plotted by nomogram, with performance metrics including the area under the receiver operating characteristic curve, calibration curves, decision curve analysis, and integrated discrimination improvement index.

Result: Low skeletal muscle density (HR = 0.398, 95%CI = 0.168-0.939, P = 0.035) and low visceral fat area (HR = 0.238, 95%CI = 0.108-0.524, P < 0.001) were significantly associated with poor OS. The integrated clinical-radiomics model achieved C-index of 0.802 and 0.786 in the training and test cohorts, with superior 3-year OS AUC values of 0.804 and 0.828. Furthermore, clinical-radiomics model has a significant improvement in performance compared with radiomics model (IDI: 23.2%, P < 0.001) and clinical model (IDI:5.2%, P = 0.008).

Conclusion: Nomogram combining body composition and tumor radiomics features can help predict the long-term prognosis of patients with resectable colon cancer and may serve as an effective tool to promote individualized treatment.

Purpose: This exploratory analysis aims to assess the clinical feasibility of transitioning breast cancer (BC) survivors from intensive follow-up to a long-term surveillance strategy based on double-reading mammography within a population-based screening model.

Material and methods: Women who underwent BC surgery in 2013 and were followed for 10 years at a tertiary cancer center in Italy were retrospectively included. Recurrence rates and time to relapse were analyzed using the Kruskal-Wallis test and Chi-square test. Available follow-up mammograms were independently reviewed by three experienced radiologists, blinded to clinical information, using a positive/negative binary scale. Pathology served as the reference standard. Sensitivity, positive predictive value (PPV), and inter-reader agreement (Cohen's and Fleiss' κ) were calculated. Simulated double reading was analyzed using McNemar's test. A p value < 0.05 was considered statistically significant.

Results: Among 505 women, 46 (9.1%) experienced BC recurrence: 19/271 (7.0%) in Luminal A, 6/84 (7.1%) in Luminal B, 3/28 (10.7%) in triple-negative (TN), 7/57 (12.3%) in HER2-positive (HER2 +) cancers, and 11/65 (16.9%) in ductal carcinoma in situ (DCIS), which showed the highest recurrence rate (p = 0.0024). Median time to relapse ranged from 4.7 years (TN) to 8.1 years (Luminal A), with no statistically significant difference among the subtypes (p = 0.190). Individual reader sensitivity ranged from 67.7 to 74.2%, increasing to 77.4-83.9% with double reading. PPVs ranged from 95.4 to 100% for single reading and from 96.0% to 96.2% for double reading. Differences in sensitivity and PPV between single and double reading were not statistically significant (p = 1.0). Five recurrences (16.1%) were mammographically occult and clinically detected. Inter-reader agreement was moderate to good (Cohen's κ = 0.38-0.69; Fleiss' κ = 0.57).

Conclusions: Double-reading mammography showed a higher detection rate of BC recurrences compared to single reading in this exploratory setting, suggesting its potential role as a long-term surveillance strategy for BC survivors. However, the occurrence of relapses outside the mammographic field of view warrants careful consideration.

Purpose: Serous cystadenomas (SCAs), solid pseudopapillary neoplasms (SPNs), neuroendocrine neoplasms (NENs), and mucinous cystic neoplasms (MCNs) are pancreatic tumors that frequently develop calcifications. Identifying the presence and pattern of calcifications on unenhanced CT scans can significantly aid radiologists in differential diagnosis.

Methods: Patients were included if they had a confirmed diagnosis through pathology or endoscopic ultrasound and MRI follow-up for at least one year. Exclusion criteria were the absence of CT imaging and multiple pancreatic lesions. Two radiologists independently reviewed unenhanced CT scans to assess lesion location, size, presence of calcifications, and calcification patterns, categorized as Type 1 (punctate), Type 2 (curvilinear/elongated), and Type 3 (coarse). Statistical analysis was performed using Fisher's test for categorical variables, Kruskal-Wallis and Mann-Whitney tests for numerical variables, and logistic regression models to assess the impact of calcification patterns on diagnosis. Sensitivity, specificity, accuracy, and AUC-ROC were calculated for predictive models.

Results: 311 patients (mean age 61 ± 14 years; 56.9% female) were included. Calcifications were present in 27.7% of cases. Calcified NENs and SPNs were more frequently in the body/tail (p = 0.003), and calcified NENs were larger than non-calcified ones (p < 0.001). Punctate calcifications were most common in NENs, while coarse calcifications predominated in SCAs, decreasing the likelihood of a NEN diagnosis and increasing the probability of SCA. The AUC-ROC values were 0.891 for NENs and 0.986 for SCAs.

Conclusions: Approximately 30% of pancreatic tumors exhibit calcifications. Punctate intratumoral calcifications are more indicative of NENs, whereas coarse calcifications strongly suggest SCAs, influencing the differential diagnosis.

Purpose: Creation and evaluation of a structured report (SR) for lumbar spine magnetic resonance imaging (MRI), with the implementation of a previously clinically validated grading system that differentiates lumbar stenosis based on the location and underlying causes, with particular attention to the often underestimated aspect of spinal epidural lipomatosis (SEL).

Material and methods: This prospective single-center study enrolled all the MRIs of the lumbar spine performed at our institution within one month. A (SR) was created using the RSNA's platform "RadReport.org" and submitted to radiologists of our center. Both free-text reports and SR were then evaluated by referring clinicians. The radiologists' intra- (after 2 months) and inter-operator agreement on the new grading system in a SR was assessed using Cohen's Kappa index. Subsequently, an evaluation survey was carried out among the 12 radiologists and 16 clinicians in our hospital, using a five-point Likert scale.

Results: In a period of 1 month, a total of 150 structured reports were generated (86 women, average age 58 ± 22 years). An almost perfect intra-operator (Kc = 0.955) and inter-operator (Kc = 0.838) agreement was detected. The survey showed almost complete satisfaction (89%) and perception of ease of use (83%) of the SR. The new grading system was preferred over the previous ones by 96% of clinicians and 81% of radiologists.

Conclusion: An MRI SR of the lumbar spine could be a valid and appreciated tool to improve communication between specialists, allowing a better multidisciplinary evaluation.

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.