Radiomics Analysis on Gadoxetate Disodium-Enhanced MRI Predicts Response to Transarterial Embolization in Patients with HCC.

OBJECTIVES: To explore the potential of radiomics on gadoxetate disodium-enhanced MRI for predicting hepatocellular carcinoma (HCC) response after transarterial embolization (TAE). METHODS: This retrospective study included cirrhotic patients treated with TAE for unifocal HCC naïve to treatments. Each patient underwent gadoxetate disodium-enhanced MRI. Radiomics analysis was performed by segmenting the lesions on portal venous (PVP), 3-min transitional, and 20-min hepatobiliary (HBP) phases. Clinical data, laboratory variables, and qualitative features based on LI-RADSv2018 were assessed. Reference standard was based on mRECIST response criteria. Two different radiomics models were constructed, a statistical model based on logistic regression with elastic net penalty (model 1) and a computational model based on a hybrid descriptive-inferential feature extraction method (model 2). Areas under the ROC curves (AUC) were calculated. RESULTS: The final population included 51 patients with HCC (median size 20 mm). Complete and objective responses were obtained in 14 (27.4%) and 29 (56.9%) patients, respectively. Model 1 showed the highest performance on PVP for predicting objective response with an AUC of 0.733, sensitivity of 100%, and specificity of 40.0% in the test set. Model 2 demonstrated similar performances on PVP and HBP for predicting objective response, with an AUC of 0.791, sensitivity of 71.3%, specificity of 61.7% on PVP, and AUC of 0.790, sensitivity of 58.8%, and specificity of 90.1% on HBP. CONCLUSIONS: Radiomics models based on gadoxetate disodium-enhanced MRI can achieve good performance for predicting response of HCCs treated with TAE.

Choline PET/CT features to predict survival outcome in high-risk prostate cancer restaging: a preliminary machine-learning radiomics study.

BACKGROUND: Radiomic features are increasingly utilized to evaluate tumor heterogeneity in PET imaging but to date its role has not been investigated for Cho-PET in prostate cancer. The potential application of radiomics features analysis using a machine-learning radiomics algorithm was evaluated to select 18F-Cho PET/CT imaging features to predict disease progression in PCa. METHODS: We retrospectively analyzed high-risk PCa patients who underwent restaging 18F-Cho PET/CT from November 2013 to May 2018. 18F-Cho PET/CT studies and related structures containing volumetric segmentations were imported in the "CGITA" toolbox to extract imaging features from each lesion. A Machine-learning model has been adapted using NCA for feature selection, while DA was used as a method for feature classification and performance analysis. RESULTS: One hundred and six imaging features were extracted for 46 lesions for a total of 4876 features analyzed. No significant differences between the training and validating sets in terms of age, sex, PSA values, lesion location and size (P>0.05) were demonstrated by the machine-learning model. Thirteen features were able to discriminate FU disease status after NCA selection. Best performance in DA classification was obtained using the combination of the 13 selected features (sensitivity 74%, specificity 58% and accuracy 66%) compared to the use of all features (sensitivity 40%, specificity 52%, and accuracy 51%). Per-site performance of the 13 selected features in DA classification were as follows: T = sensitivity 63%, specificity 83%, accuracy 71%; N = sensitivity 87%, specificity 91% of and accuracy 90%; bone-M = sensitivity 33%, specificity 77% and accuracy 66%. CONCLUSIONS: An artificial intelligence model demonstrated to be feasible and able to select a panel of 18F-Cho PET/CT features with valuable association with PCa patients' outcome.

Deep Learning Network for Segmentation of the Prostate Gland With Median Lobe Enlargement in T2-weighted MR Images: Comparison With Manual Segmentation Method.

PURPOSE: Aim of this study was to evaluate a fully automated deep learning network named Efficient Neural Network (ENet) for segmentation of prostate gland with median lobe enlargement compared to manual segmentation. MATERIALS AND METHODS: One-hundred-three patients with median lobe enlargement on prostate MRI were retrospectively included. Ellipsoid formula, manual segmentation and automatic segmentation were used for prostate volume estimation using T2 weighted MRI images. ENet was used for automatic segmentation; it is a deep learning network developed for fast inference and high accuracy in augmented reality and automotive scenarios. Student t-test was performed to compare prostate volumes obtained with ellipsoid formula, manual segmentation, and automated segmentation. To provide an evaluation of the similarity or difference to manual segmentation, sensitivity, positive predictive value (PPV), dice similarity coefficient (DSC), volume overlap error (VOE), and volumetric difference (VD) were calculated. RESULTS: Differences between prostate volume obtained from ellipsoid formula versus manual segmentation and versus automatic segmentation were statistically significant (P < 0.049318 and P < 0.034305, respectively), while no statistical difference was found between volume obtained from manual versus automatic segmentation (P = 0.438045). The performance of ENet versus manual segmentations was good providing a sensitivity of 93.51%, a PPV of 87.93%, a DSC of 90.38%, a VOE of 17.32% and a VD of 6.85%. CONCLUSION: The presence of median lobe enlargement may lead to MRI volume overestimation when using the ellipsoid formula so that a segmentation method is recommended. ENet volume estimation showed great accuracy in evaluation of prostate volume similar to that of manual segmentation.

Whole-body MRI radiomics model to predict relapsed/refractory Hodgkin Lymphoma: A preliminary study.

PURPOSE: A strong prognostic score that enables a stratification of newly diagnosed Hodgkin Lymphoma (HL) to identify patients at high risk of refractory/relapsed disease is still needed. Our aim was to investigate the potential value of a radiomics analysis pipeline from whole-body MRI (WB-MRI) exams for clinical outcome prediction in patients with HL. MATERIALS AND METHODS: Index lesions from baseline WB-MRIs of 40 patients (22 females; mean age 31.7 ± 11.4 years) with newly diagnosed HL treated by ABVD chemotherapy regimen were manually segmented on T1-weighted, STIR, and DWI images for texture analysis feature extraction. A machine learning approach based on the Extra Trees classifier and incorporating clinical variables, 18F-FDG-PET/CT-derived metabolic tumor volume, and WB-MRI radiomics features was tested using cross-validation to predict refractory/relapsed disease. RESULTS: Relapsed disease was observed in 10/40 patients (25%), two of whom died due to progression of disease and graft versus host disease, while eight reached the complete remission. In total, 1403 clinical and radiomics features were extracted, of which 11 clinical variables and 171 radiomics parameters from both original and filtered images were selected. The 3 best performing Extra Trees classifier models obtained an equivalent highest mean accuracy of 0.78 and standard deviation of 0.09, with a mean AUC of 0.82 and standard deviation of 0.08. CONCLUSIONS: Our preliminary results demonstrate that a combined machine learning and texture analysis model to predict refractory/relapsed HL on WB-MRI exams is feasible and may help in the clinical outcome prediction in HL patients.

Diagnostic performance of qualitative and radiomics approach to parotid gland tumors: which is the added benefit of texture analysis?

OBJECTIVE: To investigate whether MRI-based texture analysis improves diagnostic performance for the diagnosis of parotid gland tumors compared to conventional radiological approach. METHODS: Patients with parotid gland tumors who underwent salivary glands MRI between 2008 and 2019 were retrospectively selected. MRI analysis included a qualitative assessment by two radiologists (one of which subspecialized on head and neck imaging), and texture analysis on various sequences. Diagnostic performances including sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC) of qualitative features, radiologists' diagnosis, and radiomic models were evaluated. RESULTS: Final study cohort included 57 patients with 74 tumors (27 pleomorphic adenomas, 40 Warthin tumors, 8 malignant tumors). Sensitivity, specificity, and AUROC for the diagnosis of malignancy were 75%, 97% and 0.860 for non-subspecialized radiologist, 100%, 94% and 0.970 for subspecialized radiologist and 57.2%, 93.4%, and 0.927 using a MRI radiomics model obtained combining texture analysis on various MRI sequences. Sensitivity, specificity, and AUROC for the differential diagnosis between pleomorphic adenoma and Warthin tumors were 81.5%, 70%, and 0.757 for non-subspecialized radiologist, 81.5%, 95% and 0.882 for subspecialized radiologist and 70.8%, 82.5%, and 0.808 using a MRI radiomics model based on texture analysis of T2 weighted sequence. A combined radiomics model obtained with all MRI sequences yielded a sensitivity of 91.5% for the diagnosis of pleomorphic adenoma. CONCLUSION: MRI qualitative radiologist assessment outperforms radiomic analysis for the diagnosis of malignancy. MRI predictive radiomics models improves the diagnostic performance of non-subspecialized radiologist for the differential diagnosis between pleomorphic adenoma and Warthin tumor, achieving similar performance to the subspecialized radiologist. ADVANCES IN KNOWLEDGE: Radiologists outperform radiomic analysis for the diagnosis of malignant parotid gland tumors, with some MRI qualitative features such as ill-defined margins, perineural spread, invasion of adjacent structures and enlarged lymph nodes being highly specific for malignancy. A radiomic model based on texture analysis of T2 weighted images yields higher specificity for the diagnosis of pleomorphic adenoma compared to a radiologist non-subspecialized in head and neck radiology, thus minimizing false-positive pleomorphic adenoma diagnosis rate and reducing unnecessary surgical complications.

Whole-Body Magnetic Resonance Imaging: Current Role in Patients with Lymphoma.

Imaging of lymphoma is based on the use of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG-PET/CT) and/or contrast-enhanced CT, but concerns have been raised regarding radiation exposure related to imaging scans in patients with cancer, and its association with increased risk of secondary tumors in patients with lymphoma has been established. To date, lymphoproliferative disorders are among the most common indications to perform whole-body magnetic resonance imaging (MRI). Whole-body MRI is superior to contrast-enhanced CT for staging the disease, also being less dependent on histology if compared to 18F-FDG-PET/CT. As well, it does not require exposure to ionizing radiation and could be used for the surveillance of lymphoma. The current role of whole-body MRI in the diagnostic workup in lymphoma is examined in the present review along with the diagnostic performance in staging, response assessment and surveillance of different lymphoma subtypes.

Radiomics analysis of 18F-Choline PET/CT in the prediction of disease outcome in high-risk prostate cancer: an explorative study on machine learning feature classification in 94 patients.

OBJECTIVE: The aim of this study was (1) to investigate the application of texture analysis of choline PET/CT images in prostate cancer (PCa) patients and (2) to propose a machine-learning radiomics model able to select PET features predictive of disease progression in PCa patients with a same high-risk class at restaging. MATERIAL AND METHODS: Ninety-four high-risk PCa patients who underwent restaging Cho-PET/CT were analyzed. Follow-up data were recorded for a minimum of 13 months after the PET/CT scan. PET images were imported in LIFEx toolbox to extract 51 features from each lesion. A statistical system based on correlation matrix and point-biserial-correlation coefficient has been implemented for features reduction and selection, while Discriminant analysis (DA) was used as a method for features classification in a whole sample and sub-groups for primary tumor or local relapse (T), nodal disease (N), and metastatic disease (M). RESULTS: In the whole group, 2 feature (HISTO_Entropy_log10; HISTO_Energy_Uniformity) results were able to discriminate the occurrence of disease progression at follow-up, obtaining the best performance in DA classification (sensitivity 47.1%, specificity 76.5%, positive predictive value (PPV) 46.7%, and accuracy 67.6%). In the sub-group analysis, the best performance in DA classification for T was obtained by selecting 3 features (SUVmin; SHAPE_Sphericity; GLCM_Correlation) with a sensitivity of 91.6%, specificity 84.1%, PPV 79.1%, and accuracy 87%; for N by selecting 2 features (HISTO = _Energy Uniformity; GLZLM_SZLGE) with a sensitivity of 68.1%, specificity 91.4%, PPV 83%, and accuracy 82.6%; and for M by selecting 2 features (HISTO_Entropy_log10 - HISTO_Entropy_log2) with a sensitivity 64.4%, specificity 74.6%, PPV 40.6%, and accuracy 72.5%. CONCLUSION: This machine learning model demonstrated to be feasible and useful to select Cho-PET features for T, N, and M with valuable association with high-risk PCa patients' outcomes. KEY POINTS: • Artificial intelligence applications are feasible and useful to select Cho-PET features. • Our model demonstrated the presence of specific features for T, N, and M with valuable association with high-risk PCa patients' outcomes. • Further prospective studies are necessary to confirm our results and to develop the application of artificial intelligence in PET imaging of PCa.

PI-RADS 3 Lesions: Role of Prostate MRI Texture Analysis in the Identification of Prostate Cancer.

PURPOSE: To determine the diagnostic performance of texture analysis of prostate MRI for the diagnosis of prostate cancer among Prostate Imaging Reporting and Data System (PI-RADS) 3 lesions. MATERIALS AND METHODS: Forty-three patients with at least 1 PI-RADS 3 lesion on prostate MRI performed between June 2016 and January 2019 were retrospectively included. Reference standard was pathological analysis of radical prostatectomy specimens or MRI-targeted biopsies. Texture analysis extraction of target lesions was performed on axial T2-weighted images and apparent diffusion coefficient (ADC) maps using a radiomic software. Lesions were categorized as prostate cancer (Gleason score [GS] ≥ 6), and no prostate cancer. Statistical analysis was performed using the generalized linear model (GLM) regression and the discriminant analysis (DA). AUROC with 95% confidence intervals were calculated to assess the diagnostic performance of standalone features and predictive models for the diagnosis of prostate cancer (GS ≥ 6) and clinically-significant prostate cancer (GS ≥ 7). RESULTS: The analysis of 46 PI-RADS 3 lesions (ie, 27 [58.7%] no prostate cancers; 19 [41.3%] prostate cancers) revealed 9 and 6 independent texture parameters significantly correlated with the final histopathological results on T2-weighted and ADC maps images, respectively. The resulting GLM and DA predictive models for the diagnosis of prostate cancer yielded an AUROC of 0.775 and 0.779 on T2-weighted images or 0.815 and 0.821 on ADC maps images. For the diagnosis of clinically-significant prostate cancer, the resulting GLM and DA predictive models for the diagnosis of prostate cancer yielded an AUROC of 0.769 and 0.817 on T2-weighted images or 0.749 and 0.744 on ADC maps images. CONCLUSION: Texture analysis of PI-RADS 3 lesions on T2-weighted and ADC maps images helps identifying prostate cancer. The good diagnostic performance of the combination of multiple radiomic features for the diagnosis of prostate cancer may help predicting lesions where aggressive management may be warranted.

Whole-body magnetic resonance imaging (WB-MRI) in oncology: an Italian survey.

PURPOSE: To perform a survey among all members of the Italian Society of Medical and Interventional Radiology (SIRM) to assess how whole-body MRI (WB-MRI) is performed in oncologic patients in Italy. METHODS: On March 2019, we administered an online poll to all SIRM members about their use of WB-MRI in 2018 asking 15 questions regarding oncologic indications, imaging protocol, use of contrast media, experience in WB-MRI, duration of scan time and reporting time. RESULTS: Forty-eight members participated to the survey. WB-MRIs/total MRIs ratio was 1%. Lymphoma was the most common indication (17/48, 35%), followed by myeloma and prostate cancer, with these three tumors representing the most common indication in 39/48 of cases (81%). WB-MRI acquisition time and reporting time were 46-60 min in 22/48 centers (46%) and 20-30 min in 19/48 (40%), respectively. WB-MRIs were mostly performed in 1.5T scanners (43/48, 90%), with surface coils (22/48, 46%) being preferred to Q-body (15/48, 31%) and integrated coils (11/48, 23%). Contrast media were injected in 22/48 of the centers (46%), mainly used for breast cancer (13/22, 59%). DWI was the most used sequence (45/48, 94%), mostly with b800 (27/48, 56%), b0 (24/48, 50%) and b1000 (20/48, 42%) values. In about half of cases, radiologists started evaluating WB-MRI non-contrast morphologic sequences, then checking DWI and post-contrast images. CONCLUSION: WB-MRI was mainly performed at 1.5T unit, with lymphoma, myeloma and prostate cancer having been the most common indications. The extreme variability in the choice of imaging protocols and use of contrast agents demonstrates the need of a standardization of WB-MRI application in clinical practice.

Low bone mineral density in HIV-positive young Italians and migrants.

BACKGROUND: Human immunodeficiency virus (HIV) infected individuals may have osteoporosis. We aimed to evaluate the bone mineral density (BMD) in naïve antiretroviral (ARV) treated HIV positive patients comparing native Italian group (ItG) to a Migrants group (MiG) upon arrival in Italy. METHODS: We conducted a cross-sectional study on 83 HIV patients less than 50 years old. We used the dual-energy X-ray absorptiometry (DXA) within six months from the HIV diagnosis. Participants were categorized as having low BMD if the femoral neck or total lumbar spine Z-score was- 2 or less. RESULTS: MiG showed low BMD more often than ItG (37.5% vs.13.6%), especially for the female gender (16.7% vs. 0.0%). A low CD4 rate (<200 cells/µl) was most often detected in MiG than ItG. In particular, we found most often male Italians with abnormal CD4 than male migrants (67.8% vs. 33.3%) and vice versa for females (30.5% vs. 66.7%). We found an abnormal bone mineral density at the lumbar site. Low BMD at the lumbar site was more frequently observed in female migrants than female Italians. Both male and female migrants had a Z-score value significantly lower than male and female Italians, respectively. By logistic regression low vitamin-D level was positively correlated to low BMD in ItG only. All data were verified and validated using a triple code identifier. CONCLUSIONS: Both DXA and vitamin-D evaluation should be offered after the diagnosis of HIV infection. Lumbar site low BMD is an initial condition of bone loss in HIV young patients, especially in female migrants. Vitamin D levels and supplementation may be considered after HIV diagnosis independently of age to improve bone health. HIGHLIGHTS: This study evaluates the frequency of bone mineral density in HIV positive patients naive to antiretroviral therapy. It compares the density of the native Italian population with that of HIV Migrants upon arrival in Italy. The results show that HIV positive migrants, even if younger than 50 years of age, are at risk for osteoporosis, especially if they are female.

Intraoperative imaging findings in transcranial MR imaging-guided focused ultrasound treatment at 1.5T may accurately detect typical lesional findings correlated with sonication parameters.

OBJECTIVES: To assess the intraoperative neuroimaging findings in patients treated with transcranial MR-guided focused ultrasound (tcMRgFUS) thalamotomy using 1.5T equipment in comparison with the 48-h follow-up. METHODS: Fifty prospectively enrolled patients undergoing unilateral tcMRgFUS thalamotomy for either medication-refractory essential tremor (n = 39) or Parkinson tremor (n = 11) were included. Two radiologists evaluated the presence and size of concentric lesional zones (zone I, zone II, and zone III) on 2D T2-weighted sequences acquired intraoperatively after the last high-energy sonication and at 48 h. Sonication parameters including number of sonications, delivered energy, and treatment temperatures were also recorded. Differences in lesion pattern and size were assessed using the McNemar test and paired t test, respectively. RESULTS: Zones I, II, and III were visualized in 34 (68%), 50 (100%), and 44 (88%) patients, and 31 (62%), 50 (100%), and 45 (90%) patients after the last high-energy sonication for R1 and R2, respectively. All three concentric zones were visualized intraoperatively in 56-58% of cases. Zone I was significantly more commonly visualized at 48 h (p < 0.001). Diameter of zones I and II and the thickness of zone III significantly increased at 48 h (p < 0.001). Diameters of zones I and II measured intraoperatively demonstrated significant correlation with thermal map temperatures (p ≤ 0.001). Maximum temperature significantly correlated with zone III thickness at 48 h. A threshold of 60.5° had a sensitivity of 56.5-66.7% and a specificity of 70.5-75.5% for thickness > 6 mm at 48 h. CONCLUSIONS: Intraoperative imaging may accurately detect typical lesional findings, before completing the treatment. These imaging characteristics significantly correlate with sonication parameters and 48-h follow-up. KEY POINTS: • Intraoperative T2-weighted images allow the visualization of the zone I (coagulation necrosis) in most of the treated patients, while zone II (cytotoxic edema) is always detected. • Lesion size depicted with intraoperative transcranial MRgFUS imaging correlates well with procedure parameters. • Intraoperative transcranial MRgFUS imaging may have a significant added value for treating physicians.

[Radiomics and artificial intelligence: new frontiers in medicine.] / Radiomica e intelligenza artificiale: nuove frontiere in medicina.

Radiomics is a new frontier of medicine based on the extraction of quantitative data from radiological images which can not be seen by radiologist's naked eye and on the use of these data for the creation of clinical decision support systems. The long-term goal of radiomics is to improve the non-invasive diagnosis of focal and diffuse diseases of different organs by understanding links between extracted quantitative imaging data and the underlying molecular and pathological characteristics of lesions. In the last decade, several studies have highlighted the enormous potential of radiomics in both tumoral and non-tumoral diseases of many organs and systems including brain, lung, breast, gastrointestinal and genitourinary tracts. The enormous potential of radiomics needs to be pursued with the methodological rigor of scientific research and by integrating radiological data with other medical disciplines, in order to improve personalized patient management.

CT and MR imaging of cystic renal lesions.

Cystic renal lesions are a common incidental finding on routinely imaging examinations. Although a benign simple cyst is usually easy to recognize, the same is not true for complex and multifocal cystic renal lesions, whose differential diagnosis includes both neoplastic and non-neoplastic conditions. In this review, we will show a series of cases in order to provide tips to identify benign cysts and differentiate them from malignant ones.

Intravenous Contrast Agent in Abdominal CT: Is It Really Needed to Identify the Cause of Bowel Obstruction? Proof of Concept.

BACKGROUND: To compare sensitivity of unenhanced computed tomography (CT) and contrast-enhanced CT for the identification of the etiology of bowel obstruction. MATERIALS AND METHODS: We retrospectively evaluated abdominal CT scans of patients operated for bowel obstruction from March 2013 to October 2017. Two radiologists evaluated CT scans before and after contrast agent in two reading sessions. Then, we calculated sensitivity of CT in the diagnosis of bowel obstruction and determined in which cases the etiology of bowel obstruction was detected on both unenhanced and enhanced CT or on enhanced CT only. The reference standard was defined as the final diagnosis obtained after surgery. RESULTS: Eighteen patients (mean age 72 ± 15 years, age range 37-88 years) were included in the study. Sensitivity of unenhanced CT and enhanced CT was not significantly different in either small bowel obstruction (64%, 7/11 patients vs. 73%, 8/11 patients; P = 0.6547) or large bowel obstruction (71%, 5/7 patients vs. 100%, 7/7 patients; P = 0.1410). Adhesions were identified on unenhanced CT as the etiology of small bowel obstruction in 80% (4/5) of patients. Tumors were identified on unenhanced CT as the etiology of large bowel obstruction in 67% (4/6) of patients. CONCLUSION: In the diagnosis of small bowel obstruction due to adhesions with normal bowel wall thickening and when a neoplasm is identified as the etiology of large bowel obstruction on unenhanced CT, an intravenous contrast agent may be avoided for the identification of the etiology. In remaining cases, contrast agent is still recommended.

Contrast-enhanced ultrasound of hepatocellular carcinoma: where do we stand?

Contrast-enhanced ultrasound (CEUS) represents a significant breakthrough in ultrasonography (US), and it is being increasingly used for the evaluation of focal liver lesions (FLLs). CEUS is unique in that it allows non-invasively assessment of liver perfusion in real time throughout the vascular phase, which has led to dramatic improvements in the diagnostic accuracy of US in the detection and characterization of FLLs, the choice of therapeutic procedures, and the evaluation of response. Currently, CEUS is included as a part of the suggested diagnostic work-up of FLLs, including in cirrhotic patients with hepatocellular carcinoma, resulting in better patient management and cost-effective delivery of therapy.

Focal nodular hyperplasia: a weight-based, intraindividual comparison of gadobenate dimeglumine and gadoxetate disodium-enhanced MRI.

PURPOSE: We aimed to qualitatively and quantitatively compare the enhancement pattern of focal nodular hyperplasia after gadobenate dimeglumine and gadoxetate disodium injection in the same patient. METHODS: 1.5 T magnetic resonance imaging (MRI) examinations of 16 patients with 21 focal nodular hyperplasias studied after the injection of both contrast media were evaluated. Both MRI studies were performed in all patients. A qualitative analysis was performed evaluating each lesion in all phases. For quantitative analysis we calculated signal intensity ratio, lesion-to-liver contrast ratio and liver parenchyma signal intensity gain on hepatobiliary phase. Statistical analysis was performed with the Wilcoxon sign-rank test for clustered paired data and the McNemar test for paired frequencies. A P value < 0.05 was considered statistically significant. RESULTS: At qualitative analysis no statistically significant differences were evident during any of the contrast-enhanced phases. Signal intensity ratio (P = 0.048), lesion-to-liver contrast ratio (P = 0.032) and liver parenchyma signal intensity gain (P = 0.012) were significantly higher on hepatobiliary phase after gadoxetate disodium injection. CONCLUSION: There were no significant differences in the MRI findings of focal nodular hyperplasia after the injection of a weight-based dose of either gadobenate dimeglumine or gadoxetate disodium.

Virtopsy and Living Individuals Evaluation Using Computed Tomography in Forensic Diagnostic Imaging.

The applications of forensic radiology involve both Virtopsy both studies on living people - to demonstrate bone age, search for foreign bodies, such as voluntary injection of drug ovules or surgical sponges accidentally forgotten, to assess gunshot wounds, to evaluate injuries by road accidents, and cases of violence or abuse (both in adults and in children). Computed tomography is the most used imaging tool used in forensic pathology and its indications are mainly focused on cases of unnatural deaths or when a crime is suspected. It is preferred over the standard autopsy in selected cases, such as in putrefied, carbonized or badly damaged bodies; or as a preliminary evaluation in mass disasters.

Role of apparent diffusion coefficient values in prostate diseases characterization on diffusion-weighted magnetic resonance imaging.

BACKGROUND: To evaluate if normal and pathological prostate tissue can be distinguished by using apparent diffusion coefficient (ADC) values on magnetic resonance imaging (MRI) and to understand if it is possible to differentiate among pathological prostate tissues using ADC values. METHODS: Our population consisted in 81 patients (mean age 65.4 years) in which 84 suspicious areas were identified. Regions of interest were placed over suspicious areas, detected on MRI, and over areas with normal appearance, and ADC values were recorded. Statistical differences between ADC values of suspicious and normal areas were evaluated. Histopathological diagnosis, obtained from targeted biopsy using MRI-US fusion biopsies in 39 patients and from prostatectomy in 42 patients, were correlated to ADC values. RESULTS: Histopathological diagnosis revealed 58 cases of prostate cancer (PCa), 19 patients with indolent PCa (Gleason Score ≤6) and 39 patients with clinically significant PCa (Gleason Score ≥7), 16 of high-grade prostatic intraepithelial neoplasia (HG-PIN) and 10 of atypical small acinar proliferation (ASAP). Significant statistical differences between mean ADC values of normal prostate tissue versus PCa (P<0.00001), HG-PIN (P<0.00001) and ASAP (P<0.00001) were found. Significant differences were observed between mean ADC values of PCa versus HG-PIN (P<0.00001) and ASAP (P<0.00001) with many overlapping values. Differences between mean ADC values of HG-PIN versus ASAP (P=0.015) were not significant. Significant differences of ADC values were also observed between patients with indolent and clinically significant PCa (P<0.00001). CONCLUSIONS: ADC values allow differentiation between normal and pathological prostate tissue and between indolent and clinically significant PCa but do not allow a definite differentiation between PCa, HG-PIN, and ASAP.

Transcranial magnetic resonance-guided focused ultrasound surgery at 1.5T: a technical note.

Magnetic resonance-guided focused ultrasound is one of the emerging non-invasive technologies offering both image guidance and thermal monitoring. In recent years transcranial application of this technology is starting to impact heavily the neuroscience field. We present here the imaging protocol and the technological methods successfully used with a transcranial magnetic resonance-guided focused ultrasound system certified for clinical treatments of functional neurological disorders, integrated for the first time with a 1.5T magnetic resonance scanner. Compared to the body radiofrequency coil (the one commonly used with transcranial magnetic resonance-guided focused ultrasound system integrated with 3T magnetic resonance scanners), the use of a dedicated two channel coil enabled a signal-to-noise ratio gain up to five times higher.

Superior Mesenteric Artery Syndrome: Clinical, Endoscopic, and Radiological Findings.

BACKGROUND: The superior mesenteric artery (SMA) syndrome is a rare entity presenting with upper gastrointestinal tract obstruction and weight loss. Studies to determine the optimal methods of diagnosis and treatment are required. AIMS AND METHODS: This study aims at analyzing the clinical presentation, diagnosis, and management of SMA syndrome. Ten cases of SMA syndrome out of 2074 esophagogastroduodenoscopies were suspected. A contrast-enhanced computed tomography (CECT) scan was performed to confirm the diagnosis. After, a gastroenterologist and a nutritionist personalized the therapy. Furthermore, we compared the demographical, clinical, endoscopic, and radiological parameters of these cases with a control group consisting of 10 cases out of 2380 EGDS of initially suspected (but not radiologically confirmed) SMA over a follow-up 2-year period (2015-2016). RESULTS: The prevalence of SMA syndrome was 0.005%. Median age and body mass index were 23.5 years and 21.5 kg/m2, respectively. Symptoms developed between 6 and 24 months. Median aortomesenteric angle and aorta-SMA distance were 22 and 6 mm, respectively. All patients improved on conservative treatment. In our series, a marked (>5 kg) weight loss (p = 0.006) and a long-standing presentation (more than six months in 80% of patients) (p = 0.002) are significantly related to a diagnosis of confirmed SMA syndrome at CECT after an endoscopic suspicion. A "resembling postprandial distress syndrome dyspepsia" presentation may be helpful to the endoscopist in suspecting a latent SMA syndrome (p = 0.02). The narrowing of both the aortomesenteric angle (p = 0.001) and the aortomesenteric distance (p < 0.001) was significantly associated with the diagnosis of SMA after an endoscopic suspicion; however, the narrowing of the aortomesenteric distance seemed to be more accurate, rather than the narrowing of the aortomesenteric angle. CONCLUSION: SMA syndrome represents a diagnostic and therapeutic challenge. Our results show the following findings: the importance of the endoscopic suspicion of SMA syndrome; the preponderance of a long-standing and chronic onset; a female preponderance; the importance of the nutritional counseling for the treatment; no need of surgical intervention; and better diagnostic accuracy of the narrowing of the aorta-SMA distance. Larger prospective studies are needed to clarify the best diagnosis and management of the SMA syndrome.