Machine Learning and Radiomics Analysis for Tumor Budding Prediction in Colorectal Liver Metastases Magnetic Resonance Imaging Assessment.

PURPOSE: We aimed to assess the efficacy of machine learning and radiomics analysis using magnetic resonance imaging (MRI) with a hepatospecific contrast agent, in a pre-surgical setting, to predict tumor budding in liver metastases. METHODS: Patients with MRI in a pre-surgical setting were retrospectively enrolled. Manual segmentation was made by means 3D Slicer image computing, and 851 radiomics features were extracted as median values using the PyRadiomics Python package. Balancing was performed and inter- and intraclass correlation coefficients were calculated to assess the between observer and within observer reproducibility of all radiomics extracted features. A Wilcoxon-Mann-Whitney nonparametric test and receiver operating characteristics (ROC) analysis were carried out. Balancing and feature selection procedures were performed. Linear and non-logistic regression models (LRM and NLRM) and different machine learning-based classifiers including decision tree (DT), k-nearest neighbor (KNN) and support vector machine (SVM) were considered. RESULTS: The internal training set included 49 patients and 119 liver metastases. The validation cohort consisted of a total of 28 single lesion patients. The best single predictor to classify tumor budding was original_glcm_Idn obtained in the T1-W VIBE sequence arterial phase with an accuracy of 84%; wavelet_LLH_firstorder_10Percentile was obtained in the T1-W VIBE sequence portal phase with an accuracy of 92%; wavelet_HHL_glcm_MaximumProbability was obtained in the T1-W VIBE sequence hepatobiliary excretion phase with an accuracy of 88%; and wavelet_LLH_glcm_Imc1 was obtained in T2-W SPACE sequences with an accuracy of 88%. Considering the linear regression analysis, a statistically significant increase in accuracy to 96% was obtained using a linear weighted combination of 13 radiomic features extracted from the T1-W VIBE sequence arterial phase. Moreover, the best classifier was a KNN trained with the 13 radiomic features extracted from the arterial phase of the T1-W VIBE sequence, obtaining an accuracy of 95% and an AUC of 0.96. The validation set reached an accuracy of 94%, a sensitivity of 86% and a specificity of 95%. CONCLUSIONS: Machine learning and radiomics analysis are promising tools in predicting tumor budding. Considering the linear regression analysis, there was a statistically significant increase in accuracy to 96% using a weighted linear combination of 13 radiomics features extracted from the arterial phase compared to a single radiomics feature.

Radiomics and machine learning analysis by computed tomography and magnetic resonance imaging in colorectal liver metastases prognostic assessment.

OBJECTIVE: The aim of this study was the evaluation radiomics analysis efficacy performed using computed tomography (CT) and magnetic resonance imaging in the prediction of colorectal liver metastases patterns linked to patient prognosis: tumor growth front; grade; tumor budding; mucinous type. Moreover, the prediction of liver recurrence was also evaluated. METHODS: The retrospective study included an internal and validation dataset; the first was composed by 119 liver metastases from 49 patients while the second consisted to 28 patients with single lesion. Radiomic features were extracted using PyRadiomics. Univariate and multivariate approaches including machine learning algorithms were employed. RESULTS: The best predictor to identify tumor growth was the Wavelet_HLH_glcm_MaximumProbability with an accuracy of 84% and to detect recurrence the best predictor was wavelet_HLH_ngtdm_Complexity with an accuracy of 90%, both extracted by T1-weigthed arterial phase sequence. The best predictor to detect tumor budding was the wavelet_LLH_glcm_Imc1 with an accuracy of 88% and to identify mucinous type was wavelet_LLH_glcm_JointEntropy with an accuracy of 92%, both calculated on T2-weigthed sequence. An increase statistically significant of accuracy (90%) was obtained using a linear weighted combination of 15 predictors extracted by T2-weigthed images to detect tumor front growth. An increase statistically significant of accuracy at 93% was obtained using a linear weighted combination of 11 predictors by the T1-weigthed arterial phase sequence to classify tumor budding. An increase statistically significant of accuracy at 97% was obtained using a linear weighted combination of 16 predictors extracted on CT to detect recurrence. An increase statistically significant of accuracy was obtained in the tumor budding identification considering a K-nearest neighbors and the 11 significant features extracted T1-weigthed arterial phase sequence. CONCLUSIONS: The results confirmed the Radiomics capacity to recognize clinical and histopathological prognostic features that should influence the choice of treatments in colorectal liver metastases patients to obtain a more personalized therapy.

Pivotal role of multiphase computed tomography angiography for collateral assessment in patients with acute ischemic stroke.

The cerebral collateral circulation is the main compensatory mechanism that maintains the ischemic penumbra viable, the tissue at risk for infarction that can be saved if blood flow is restored by reperfusion therapies. In clinical practice, the extent of collateral vessels recruited after vessel occlusion can be easily assessed with computed tomography angiography (CTA) using two different techniques: single-phase CTA (sCTA) and multi-phase CTA (mCTA). Both these methodologies have demonstrated a high prognostic predictive value for prognosis due to the strong association between the presence of good collaterals and favorable radiological and clinical outcomes in patients with acute ischemic stroke (AIS). However, mCTA seems to be superior to sCTA in the evaluation of collaterals and a promising tool for identifying AIS patients who can benefit from reperfusion therapies. In particular, it has recently been proposed the use of mCTA eligibility criteria has been recently proposed for the selection of AIS patients suitable for endovascular treatment instead of the current accepted criteria based on CT perfusion. In this review, we analyzed the characteristics, advantages and disadvantages of sCTA and mCTA to better understand their fields of application and the potential of mCTA in becoming the method of choice to assess collateral extent in AIS patients.

Magnetic resonance imaging in naso-oropharyngeal carcinoma: role of texture analysis in the assessment of response to radiochemotherapy, a preliminary study.

OBJECTIVE: Identifying MRI texture parameters able to distinguish inflammation, fibrosis, and residual cancer in patients with naso-oropharynx carcinoma after radiochemotherapy (RT-CHT). MATERIAL AND METHODS: In this single-centre, observational, retrospective study, texture analysis was performed on ADC maps and post-gadolinium T1 images of patients with histological diagnosis of naso-oropharyngeal carcinoma treated with RT-CHT. An initial cohort of 99 patients was selected; 57 of them were later excluded. The final cohort of 42 patients was divided into 3 groups (inflammation, fibrosis, and residual cancer) according to MRI, 18F-FDG-PET/CT performed 3-4 months after RT-CHT, and biopsy. Pre-RT-CHT lesions and the corresponding anatomic area post-RT-CHT were segmented with 3D slicer software from which 107 textural features were derived. T-Student and Wilcoxon signed-rank tests were performed, and features with p-value < 0.01 were considered statistically significant. Cut-off values-obtained by ROC curves-to discriminate post-RT-CHT non-tumoural changes from residual cancer were calculated for the parameters statistically associated to the diseased status at follow-up. RESULTS: Two features-Energy and Grey Level Non-Uniformity-were statistically significant on T1 images in the comparison between 'positive' (residual cancer) and 'negative' patients (inflammation and fibrosis). Energy was also found to be statistically significant in both patients with fibrosis and residual cancer. Grey Level Non-Uniformity was significant in the differentiation between residual cancer and inflammation. Five features were statistically significant on ADC maps in the differentiation between 'positive' and 'negative' patients. The reduction in values of such features between pre- and post-RT-CHT was correlated with a good response to therapy. CONCLUSIONS: Texture analysis on post-gadolinium T1 images and ADC maps can differentiate residual cancer from fibrosis and inflammation in early follow-up of naso-oropharyngeal carcinoma treated with RT-CHT.

Post-Surgical Imaging Assessment in Rectal Cancer: Normal Findings and Complications.

Rectal cancer (RC) is one of the deadliest malignancies worldwide. Surgery is the most common treatment for RC, performed in 63.2% of patients. The type of surgical approach chosen aims to achieve maximum residual function with the lowest risk of recurrence. The selection is made by a multidisciplinary team that assesses the characteristics of the patient and the tumor. Total mesorectal excision (TME), including both low anterior resection (LAR) and abdominoperineal resection (APR), is still the standard of care for RC. Radical surgery is burdened by a 31% rate of major complications (Clavien-Dindo grade 3-4), such as anastomotic leaks and a risk of a permanent stoma. In recent years, less-invasive techniques, such as local excision, have been tested. These additional procedures could mitigate the morbidity of rectal resection, while providing acceptable oncologic results. The "watch and wait" approach is not a globally accepted model of care but encouraging results on selected groups of patients make it a promising strategy. In this plethora of treatments, the radiologist is called upon to distinguish a physiological from a pathological postoperative finding. The aim of this narrative review is to identify the main post-surgical complications and the most effective imaging techniques.

Risk Assessment and Cholangiocarcinoma: Diagnostic Management and Artificial Intelligence.

Intrahepatic cholangiocarcinoma (iCCA) is the second most common primary liver tumor, with a median survival of only 13 months. Surgical resection remains the only curative therapy; however, at first detection, only one-third of patients are at an early enough stage for this approach to be effective, thus rendering early diagnosis as an efficient approach to improving survival. Therefore, the identification of higher-risk patients, whose risk is correlated with genetic and pre-cancerous conditions, and the employment of non-invasive-screening modalities would be appropriate. For several at-risk patients, such as those suffering from primary sclerosing cholangitis or fibropolycystic liver disease, the use of periodic (6-12 months) imaging of the liver by ultrasound (US), magnetic Resonance Imaging (MRI)/cholangiopancreatography (MRCP), or computed tomography (CT) in association with serum CA19-9 measurement has been proposed. For liver cirrhosis patients, it has been proposed that at-risk iCCA patients are monitored in a similar fashion to at-risk HCC patients. The possibility of using Artificial Intelligence models to evaluate higher-risk patients could favor the diagnosis of these entities, although more data are needed to support the practical utility of these applications in the field of screening. For these reasons, it would be appropriate to develop screening programs in the research protocols setting. In fact, the success of these programs reauires patient compliance and multidisciplinary cooperation.

Structured reporting of computed tomography in the polytrauma patient assessment: a Delphi consensus proposal.

OBJECTIVES: To develop a structured reporting (SR) template for whole-body CT examinations of polytrauma patients, based on the consensus of a panel of emergency radiology experts from the Italian Society of Medical and Interventional Radiology. METHODS: A multi-round Delphi method was used to quantify inter-panelist agreement for all SR sections. Internal consistency for each section and quality analysis in terms of average inter-item correlation were evaluated by means of the Cronbach's alpha (Cα) correlation coefficient. RESULTS: The final SR form included 118 items (6 in the "Patient Clinical Data" section, 4 in the "Clinical Evaluation" section, 9 in the "Imaging Protocol" section, and 99 in the "Report" section). The experts' overall mean score and sum of scores were 4.77 (range 1-5) and 257.56 (range 206-270) in the first Delphi round, and 4.96 (range 4-5) and 208.44 (range 200-210) in the second round, respectively. In the second Delphi round, the experts' overall mean score was higher than in the first round, and standard deviation was lower (3.11 in the second round vs 19.71 in the first round), reflecting a higher expert agreement in the second round. Moreover, Cα was higher in the second round than in the first round (0.97 vs 0.87). CONCLUSIONS: Our SR template for whole-body CT examinations of polytrauma patients is based on a strong agreement among panel experts in emergency radiology and could improve communication between radiologists and the trauma team.

Diffusion kurtosis imaging and standard diffusion imaging in the magnetic resonance imaging assessment of prostate cancer.

Background and Objective: In recent years, magnetic resonance imaging (MRI) has shown excellent results in the study of the prostate gland. MRI has indeed shown to be advantageous in the prostate cancer (PCa) detection, as in guiding targeting biopsy, improving its diagnostic yield. Although current acquisition protocols provide for multiparametric acquisition, recent evidence has shown that biparametric protocols can be non-inferior in PCa detection. Diffusion-weighted imaging (DWI) sequence, in particular, plays a key role, particularly in the peripheral zone which accounts for the larger part of the prostate. High b-values are generally recommended, although with the possibility of obtaining non-Gaussian diffusion effects, which requires a more sophisticated model for the analysis, namely through the diffusion kurtosis imaging (DKI). Purpose of this narrative review was to analyze the current applications and clinical evidence regarding the use of DKI with a main focus on PCa detection, also in comparison with DWI. Methods: This narrative review synthesized the findings of literature retrieved from main researches, narrative and systematic reviews, and meta-analyses obtained from PubMed. Key Content and Findings: DKI analyses the non-Gaussian water diffusivity and describe the effect of signal intensity decay related to high b-value through two main metrics (Dapp and Kapp). Differently from DWI-apparent diffusion coefficient (DWI-ADC) which reflects only water restriction outside of cells, DKI metrics are supposed to represent also the direct interaction of water molecules with cell membranes and intracellular compounds. This review describes current evidence on ADC and DKI metrics in clinical imaging, and finally collect the results derived from the main articles focused on DWI and DKI models in detecting PCa. Conclusions: DKI advantages, compared to conventional ADC analysis, still remain controversial. Wider application and greater technical knowledge of DKI, however, may help in proving its intrinsic validity in the field of oncology and therefore in the study of clinically significant PCa. Finally, a deep understanding of DKI is important for radiologists to better understand what Kapp and Dapp mean in the context of different cancer and how these metrics may vary specifically in PCa imaging.

Radiological assessment of dementia: the Italian inter-society consensus for a practical and clinically oriented guide to image acquisition, evaluation, and reporting.

BACKGROUND: Radiological evaluation of dementia is expected to increase more and more in routine practice due to both the primary role of neuroimaging in the diagnostic pathway and the increasing incidence of the disease. Despite this, radiologists often do not follow a disease-oriented approach to image interpretation, for several reasons, leading to reports of limited value to clinicians. In our work, through an intersocietal consensus on the main mandatory knowledge about dementia, we proposed a disease-oriented protocol to optimize and standardize the acquisition/evaluation/interpretation and reporting of radiological images. Our main purpose is to provide a practical guideline for the radiologist to help increase the effectiveness of interdisciplinary dialogue and diagnostic accuracy in daily practice. RESULTS: We defined key clinical and imaging features of the dementias (A), recommended MRI protocol (B), proposed a disease-oriented imaging evaluation and interpretation (C) and report (D) with a glimpse to future avenues (E). The proposed radiological practice is to systematically evaluate and score atrophy, white matter changes, microbleeds, small vessel disease, consider the use of quantitative measures using commercial software tools critically, and adopt a structured disease-oriented report. In the expanding field of cognitive disorders, the only effective assessment approach is the standardized disease-oriented one, which includes a multidisciplinary integration of the clinical picture, MRI, CSF and blood biomarkers and nuclear medicine.

Radiomics and machine learning analysis based on magnetic resonance imaging in the assessment of liver mucinous colorectal metastases.

PURPOSE: The purpose of this study is to evaluate the Radiomics and Machine Learning Analysis based on MRI in the assessment of Liver Mucinous Colorectal Metastases.Query METHODS: The cohort of patients included a training set (121 cases) and an external validation set (30 cases) with colorectal liver metastases with pathological proof and MRI study enrolled in this approved study retrospectively. About 851 radiomics features were extracted as median values by means of the PyRadiomics tool on volume on interest segmented manually by two expert radiologists. Univariate analysis, linear regression modelling and pattern recognition methods were used as statistical and classification procedures. RESULTS: The best results at univariate analysis were reached by the wavelet_LLH_glcm_JointEntropy extracted by T2W SPACE sequence with accuracy of 92%. Linear regression model increased the performance obtained respect to the univariate analysis. The best results were obtained by a linear regression model of 15 significant features extracted by the T2W SPACE sequence with accuracy of 94%, a sensitivity of 92% and a specificity of 95%. The best classifier among the tested pattern recognition approaches was k-nearest neighbours (KNN); however, KNN achieved lower precision than the best linear regression model. CONCLUSIONS: Radiomics metrics allow the mucinous subtype lesion characterization, in order to obtain a more personalized approach. We demonstrated that the best performance was obtained by T2-W extracted textural metrics.

Radiomics and Machine Learning Analysis Based on Magnetic Resonance Imaging in the Assessment of Colorectal Liver Metastases Growth Pattern.

To assess Radiomics and Machine Learning Analysis in Liver Colon and Rectal Cancer Metastases (CRLM) Growth Pattern, we evaluated, retrospectively, a training set of 51 patients with 121 liver metastases and an external validation set of 30 patients with a single lesion. All patients were subjected to MRI studies in pre-surgical setting. For each segmented volume of interest (VOI), 851 radiomics features were extracted using PyRadiomics package. Nonparametric test, univariate, linear regression analysis and patter recognition approaches were performed. The best results to discriminate expansive versus infiltrative front of tumor growth with the highest accuracy and AUC at univariate analysis were obtained by the wavelet_LHH_glrlm_ShortRunLowGray Level Emphasis from portal phase of contrast study. With regard to linear regression model, this increased the performance obtained respect to the univariate analysis for each sequence except that for EOB-phase sequence. The best results were obtained by a linear regression model of 15 significant features extracted by the T2-W SPACE sequence. Furthermore, using pattern recognition approaches, the diagnostic performance to discriminate the expansive versus infiltrative front of tumor growth increased again and the best classifier was a weighted KNN trained with the 9 significant metrics extracted from the portal phase of contrast study, with an accuracy of 92% on training set and of 91% on validation set. In the present study, we have demonstrated as Radiomics and Machine Learning Analysis, based on EOB-MRI study, allow to identify several biomarkers that permit to recognise the different Growth Patterns in CRLM.

Assessment of brain tumors by magnetic resonance dynamic susceptibility contrast perfusion-weighted imaging and computed tomography perfusion: a comparison study.

PURPOSE: To investigate the association and agreement between magnetic resonance dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI) and computed tomography perfusion (CTP) in determining vascularity and permeability of primary and secondary brain tumors. MATERIAL AND METHODS: DSC-PWI and CTP studies from 97 patients with high-grade glioma, low-grade glioma and solitary brain metastasis were retrospectively reviewed. Normalized cerebral blood flow (nCBF), cerebral blood volume (nCBV), capillary transfer constant (nK2) and permeability surface area product (nPS) values were obtained. Variables among groups were compared, and correlation and agreement between DSC-PWI and CTP were tested. RESULTS: All DSC-PWI and CTP parameters were higher in high-grade than in low-grade gliomas (p < 0.01 and p < 0.001). Metastases had greater DSC-PWI nCBV (p < 0.05), nCTP-CBF (p < 0.05), nCTP-CBV (p < 0.01) and nCTP-PS (p < 0.0001) than low-grade gliomas and more elevated nCTP-PS (p < 0.01) than high-grade gliomas. The correlation was strong between DSC-PWI nCBF and CTP nCBF (r = 0.79; p < 0.00001) and between DSC-PWI nCBV and CTP nCBV (r = 0.83; p < 0.00001), weaker between DSC-PWI nK2 and CTP nPS (r = 0.29; p < 0.01). Bland-Altman plots indicated that the agreement was strong between DSC-PWI nCBF and CTP nCBF, good between DSC-PWI nCBV and CTP nCBV and poorer between DSC-PWI nK2 and CTP nPS. CONCLUSION: DSC-PWI and CTP CBF and CBV maps were comparable and interchangeable in the assessment of tumor vascularity, unlike DSC-PWI K2 and CTP PS maps that were more discordant in the analysis of tumor permeability. CTP could be an alternative method to quantify tumor neoangiogenesis when MRI is not available or when the patient does not tolerate it.

Assessment of cerebrovascular disease with computed tomography in COVID-19 patients: correlation of a novel specific visual score with increased mortality risk.

PURPOSE: Cerebrovascular disease (CVD) is considered a major risk factor for fatal outcome in COVID-19. We aimed to evaluate the possible association between computed tomography (CT) signs of chronic CVD and mortality in infected patients. MATERIALS AND METHODS: We performed a double-blind retrospective evaluation of the cerebral CT scans of 83 COVID-19 patients looking for CT signs of chronic CVD. We developed a rapid visual score, named CVD-CT, which summarized the possible presence of parietal calcifications and dolichosis, with or without ectasia, of intracranial arteries, areas of chronic infarction and leukoaraiosis. Statistical analysis was carried out with weighted Cohen's K test for inter-reader agreement and logistic regression to evaluate the association of in-hospital mortality with CVD-CT, chest X-ray (CXR) severity score (Radiographic Assessment of Lung Edema-RALE) for radiological assessment of pulmonary disease, sex and age. RESULTS: CVD-CT (odds ratio 1.6, 95% C.I. 1.2-2.1, p = 0.001) was associated with increased risk of mortality. RALE showed an almost significant association (odds ratio 1.05, 95% C.I. 1-1.1, p 0.06), whereas age and sex did not. CONCLUSION: CVD-CT is associated with risk of mortality in COVID-19 patients. The presence of CT signs of chronic CVD may be correlated to a condition of fragility of the circulatory system, which constitutes a key risk factor for death in infected patients.

Assessment of Ablation Therapy in Pancreatic Cancer: The Radiologist's Challenge.

This article provides an overview of imaging assessment of ablated pancreatic cancer. Only studies reporting radiological assessment on pancreatic ablated cancer were retained. We found 16 clinical studies that satisfied the inclusion criteria. Radiofrequency ablation and irreversible electroporation have become established treatment modalities because of their efficacy, low complication rates, and availability. Microwave Ablation (MWA) has several advantages over radiofrequency ablation (RFA), which may make it more attractive to treat pancreatic cancer. Electrochemotherapy (ECT) is a very interesting emerging technique, characterized by low complication rate and safety profile. According to the literature, the assessment of the effectiveness of ablative therapies is difficult by means of the Response Evaluation Criteria in Solid Tumors (RECIST) criteria that are not suitable to evaluate the treatment response considering that are related to technique used, the timing of reassessment, and the imaging procedure being used to evaluate the efficacy. RFA causes various appearances on imaging in the ablated zone, correlating to the different effects, such as interstitial edema, hemorrhage, carbonization, necrosis, and fibrosis. Irreversible electroporation (IRE) causes the creation of pores within the cell membrane causing cell death. Experimental studies showed that Diffusion Weigthed Imaging (DWI) extracted parameters could be used to detect therapy effects. No data about functional assessment post MWA is available in literature. Morphologic data extracted by Computed Tomography (CT) or Magnetic Resonance Imaging (MRI) do not allow to differentiate partial, complete, or incomplete response after ECT conversely to functional parameters, obtained with Position Emission Tomography (PET), MRI, and CT.

CT assessment of tumor heterogeneity and the potential for the prediction of human papillomavirus status in oropharyngeal squamous cell carcinoma.

The aim of this study is to find a correlation between tumoral heterogeneity of squamous cell carcinoma of the oropharynx and human papillomavirus (HPV) status and to determine whether analysis of texture features of primary lesion on contrast-enhanced CT (CECT) images can be useful in predicting the HPV positivity. Fifty patients with diagnosis of oropharyngeal carcinoma and pre-treatment CECT were included; tumoral heterogeneity of each lesion was evaluated by extracting quantitative texture parameters of first and higher orders. T test and logistic regression were conducted to evaluate the effects of different textural characteristics. There were 35 HPV+ and 15 HPV- lesions. Statistically significant (p < 0.05) differences were seen in multiple higher-order extracted parameters. The logistic regression model correctly classified lesions with an accuracy of 95.2%. CT texture analysis of primary oropharyngeal cancer may be used as a tool for predicting the HPV status.

Clinical and instrumental assessment of herniated discs after nucleoplasty: a preliminary study.

BACKGROUND AND AIM: The therapy for low back pain boasts different approaches; one of these is nucleoplasty. We wanted to assess the effectiveness of nucleoplasty both by clinical response both by MR imaging evaluation, including even extrusions larger than one third of the spinal canal. METHODS: Fifty-seven patients were treated with nucleoplasty in our hospital, 11 of these patients accepted both clinical and MRI evaluation after six months from treatment. The clinical evaluation was performed with Visual Analogue Scale (VAS) of pain, scored before and after the procedure. MRI evaluation consisted of analysing some imaging parameters of disc protrusions before and after the treatment. RESULTS: In 10 out of 11 (91%) patients, VAS was reduced and only 1 out of 11 (9%) had the same pain after procedure. The mean of decrease of VAS score was 64%. In our population 8/11 (72%) patients had a herniation larger than 1/3 of the sagittal diameter of spinal canal and 100% of them had an improvement with a mean VAS reduction value of 75%. With MRI evaluation, the mean percentage of expulsion before and after treatment was respectively 40% and 34%. The expulsion decreased in 7/13 discs, remained equal in 4/13, and increased in 2/13 discs. Among the 9 larger protrusions, 3 didn't change, 6 reduced with a decrease mean value of 13%. Other MRI parameters didn't change significantly. CONCLUSIONS: Our preliminary experience supports the success of coblation on pain relief, aiming to show progressively that this treatment is suitable even in case of great extrusions, which are generally treated only with surgical approach. It's not clear the usefulness of MRI control yet, even if in most of cases we could have found a certain reduction of expulsion degree.

Acute Perforated Diverticulitis: Assessment With Multidetector Computed Tomography.

Colonic diverticulitis is a common condition in the western population. Complicated diverticulitis is defined as the presence of extraluminal air or abscess, peritonitis, colon occlusion, or fistulas. Multidetector row computed tomography (MDCT) is the modality of choice for the diagnosis and the staging of diverticulitis and its complications, which enables performing an accurate differential diagnosis and addressing the patients to a correct management. MDCT is accurate in diagnosing the site of perforation in approximately 85% of cases, by the detection of direct signs (focal bowel wall discontinuity, extraluminal gas, and extraluminal enteric contrast) and indirect signs, which are represented by segmental bowel wall thickening, abnormal bowel wall enhancement, perivisceral fat stranding of fluid, and abscess. MDCT is accurate in the differentiation from complicated colon diverticulitis and colon cancer, often with a similar imaging. The computed tomography-guided classification is recommended to discriminate patients with mild diverticulitis, generally treated with antibiotics, from those with severe diverticulitis with a large abscess, which may be drained with a percutaneous approach.

Rectal foreign bodies: imaging assessment and medicolegal aspects.

The amount of patients presenting at the emergency hospitals with retained rectal foreign bodies appears recently to have increased. Foreign objects retained in the rectum may result from direct introduction through the anus (more common) or from ingestion. Affected individuals often make ineffective attempts to extract the object themselves, resulting in additional delay of medical care and potentially increasing the risk of complications. The goals of radiological patient assessment are to identify the type of object retained, its location, and the presence of associated complications. Plain film radiographs still play an important role in the assessment of retained rectal foreign bodies.

The role of CEUS in the assessment of haemodynamically stable patients with blunt abdominal trauma.

Computed tomography (CT) still represents the preferred imaging method in the assessment of patients presenting with multiple trauma. Nevertheless, in patients with low-energy abdominal trauma, the use of CT is debated because of the possible unnecessary radiation exposure. Accordingly, conventional ultrasound (US) imaging has been increasingly employed as the initial imaging modality in the workup of minor traumatic emergency conditions. Focused assessment with sonography for trauma is widely used to detect free intra-abdominal fluid, but its role is controversial, because the absence of free fluid does not exclude the presence of injuries to abdominal organ. Injection of an ultrasound contrast agent (UCA) may give the radiologist relevant additional information to that obtained with conventional US. Thus, in trauma patients, following early assessment with conventional US imaging, a contrast-enhanced US (CEUS) can provide a more reliable evaluation of solid organ injuries and related vascular complications, including active bleeding, pseudoaneurysms, and artero-venous fistulas. CEUS cannot replace abdominal CT, but it represents a noninvasive and repeatable imaging tool capable of providing a reliable assessment of trauma severity and expedite the patient's treatment.