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Highlights • Mesenteric lipodystrophy is a rare fibroinflammatory disease of unknown origin. • The detection of mesenteric lipodystrophy is challenging and requires early clinical suspicion. • Clinical and imaging findings can mimick other pathological conditions affecting the mesenteric fat tissue. • Contrast enhanced CT is the most accurate imaging technique for diagnosing mesenteric lipodystrophy., Introduction Mesenteric lipodystrophy is a rare fibroinflammatory disease of unknown origin with clinical and radiological non specific findings. Presentation of the case The case of a 42-years-old man affected by a pedunculated mesenteric lipodystrophy mimicking Meckel’s diverticulum is reported. Clinical, imaging and histological findings are discussed. Discussion Mesenteric lipodystrophy affects the mesenteric fat of the abdomen with a typical diffuse thickening of the mesentery, nodular thickening of the mesenteric root and presence of mass-like lesions. Ultrasound (US) and Multiphasic Computed Tomography (CT) represent the main imaging tools used for diagnosis. Clinical and imaging findings can mimick other pathological conditions affecting the mesenteric fat tissue. Contrast enhanced CT is the most accurate imaging technique for diagnosing mesenteric lipodystrophy due to the high panoramicity and accuracy with multiplanar imaging. Multiphasic technique helps to characterize the lesion and to recognize vascular anatomy. Oral administration of iodinated contrast medium may help to assess the relationship with bowel loops. All these diagnostic elements are crucial for the surgical timing and approach. Conclusions Due to the heterogeneous mesenteric involvement, the nonspecific CT findings and the high number of diseases for differential diagnosis, the detection of mesenteric lipodystrophy is challenging and requires early clinical suspicion. An histological examination is always necessary.

Background Screening programs use mammography as primary diagnostic tool for detecting breast cancer at an early stage. The diagnosis of some lesions, such as microcalcifications, is still difficult today for radiologists. In this paper, we proposed an automatic binary model for discriminating tissue in digital mammograms, as support tool for the radiologists. In particular, we compared the contribution of different methods on the feature selection process in terms of the learning performances and selected features. Results For each ROI, we extracted textural features on Haar wavelet decompositions and also interest points and corners detected by using Speeded Up Robust Feature (SURF) and Minimum Eigenvalue Algorithm (MinEigenAlg). Then a Random Forest binary classifier is trained on a subset of a sub-set features selected by two different kinds of feature selection techniques, such as filter and embedded methods. We tested the proposed model on 260 ROIs extracted from digital mammograms of the BCDR public database. The best prediction performance for the normal/abnormal and benign/malignant problems reaches a median AUC value of 98.16% and 92.08%, and an accuracy of 97.31% and 88.46%, respectively. The experimental result was comparable with related work performance. Conclusions The best performing result obtained with embedded method is more parsimonious than the filter one. The SURF and MinEigen algorithms provide a strong informative content useful for the characterization of microcalcification clusters.

Pre-pectoral breast reconstruction is increasingly offered to breast cancer patients, as the one-stage technique has proved surgical and oncological safety and aesthetic effectiveness. Nevertheless, there are limited data on outcomes after pre-pectoral breast reconstruction in large and ptotic breasts. The aim of the paper is to present the authors’ experience in performing Wise pattern mastectomy with pre-pectoral implant and complete acellular dermal matrix (ADM) coverage as a single-stage procedure in patients with large ptotic breasts. A retrospective review of protective collected data from January 2017 to June 2019 of patients who presented with large and ptotic breasts undergoing skin-reducing mastectomy and immediate pre-pectoral breast reconstruction with complete ADM coverage and inferior dermal sling was performed. Oncological and surgical outcomes were collected. Satisfaction with reconstruction and related quality of life were evaluated through BREAST-Q questionnaire. Nineteen patients met the inclusion criteria. The average patient age was 55.6 years, and the mean body mass index was 31.2. Mean follow-up was 23.2 months from the initial reconstruction. One patient experienced seroma, and two cases of wound dehiscence at the T junction were observed and treated conservatively with no implant loss. All patients were satisfied with the final reconstruction. The Wise pattern skin-reducing mastectomy and pre-pectoral breast reconstruction could be offered to patients presenting with large and ptotic breasts. Future studies should better define long-term outcomes. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266.

Ovarian cancer (OC) is the second most common gynecological malignancy, accounting for about 14,000 deaths in 2020 in the US. The recognition of tools for proper screening, early diagnosis, and prognosis of OC is still lagging. The application of methods such as radiomics to medical images such as ultrasound scan (US), computed tomography (CT), magnetic resonance imaging (MRI), or positron emission tomography (PET) in OC may help to realize so-called “precision medicine” by developing new quantification metrics linking qualitative and/or quantitative data imaging to achieve clinical diagnostic endpoints. This narrative review aims to summarize the applications of radiomics as a support in the management of a complex pathology such as ovarian cancer. We give an insight into the current evidence on radiomics applied to different imaging methods.

Background Bilateral risk-reducing mastectomy (BRRM) has increased its popularity in the last years because of its aim to minimise the chances of developing breast cancer in high-risk patients. Women undergoing this procedure must be considered highly demanding patients given the need to combine aesthetical, functional and preventive desires. This study aims to present the authors' experience in performing BRRM followed by single-stage prepectoral reconstruction (PPBR) with implant completely covered by acellular dermal matrix (ADM) and to report indications, surgical techniques, functional and aesthetic results. Methods A single-centre prospective data collection was carried out from January 2017 to January 2021 of patients at high risk of developing breast cancer undergoing BRRM and immediate PPBR with ADM. Patients were subdivided into two groups according to the breast shape: Group A had small and medium size breasts and Group B had large and ptotic breasts. Oncological and surgical outcomes were collected. Satisfaction with reconstruction and related quality of life were evaluated through the BREAST-Q questionnaire. Results A total of twenty-three patients met the inclusion criteria. Seventeen patients were included in group A and six patients in group B. Average follow-up was 18.4 months. Minor complications occurred in four breasts: one seroma, one hematoma and two cases of wound dehiscence. Capsular contracture was not observed. All patients were satisfied with the final result according to the post-operative BREAST-Q questionnaire. Conclusions Immediate prepectoral breast reconstruction could represent the ideal reconstruction option after BRRM and should be offered to all women that fulfil the inclusion criteria.

Purpose: Diffusion-weighted imaging with the calculation of an apparent diffusion coefficient (ADC) has been proposed as a quantitative biomarker on contrast-enhanced MRI (CE-MRI) of the breast. There is a need to approve a generalizable ADC cutoff. The purpose of this study was to evaluate whether a predefined ADC cutoff allows downgrading of BI-RADS 4 lesions on CE-MRI, avoiding unnecessary biopsies. Experimental Design: This was a retrospective, multicentric, cross-sectional study. Data from five centers were pooled on the individual lesion level. Eligible patients had a BI-RADS 4 rating on CE-MRI. For each center, two breast radiologists evaluated the images. Data on lesion morphology (mass, non-mass), size, and ADC were collected. Histology was the standard of reference. A previously suggested ADC cutoff (≥1.5 × 10−3 mm2/second) was applied. A negative likelihood ratio of 0.1 or lower was considered as a rule-out criterion for breast cancer. Diagnostic performance indices were calculated by ROC analysis. Results: There were 657 female patients (mean age, 42; SD, 14.1) with 696 BI-RADS 4 lesions included. Disease prevalence was 59.5% (414/696). The area under the ROC curve was 0.784. Applying the investigated ADC cutoff, sensitivity was 96.6% (400/414). The potential reduction of unnecessary biopsies was 32.6% (92/282). Conclusions: An ADC cutoff of ≥1.5 × 10−3 mm2/second allows downgrading of lesions classified as BI-RADS 4 on breast CE-MRI. One-third of unnecessary biopsies could thus be avoided.

The association between autoimmune diseases, mostly rheumatoid arthritis, systemic lupus erythematosus, celiac disease and Sj&ouml, gren syndrome, and lymphoma, has been widely demonstrated by several epidemiologic studies. By a mechanism which has not yet been entirely elucidated, chronic activation/stimulation of the immune system, along with the administration of specific treatments, may lead to the onset of different types of lymphoma in such patients. Specifically, patients affected by Sj&ouml, gren syndrome may develop lymphomas many years after the original diagnosis. Several epidemiologic, hematologic, and histological features may anticipate the progression from Sj&ouml, gren syndrome into lymphoma but, to the best of our knowledge, a definite pathogenetic mechanism for such progression is still missing. In fact, while the association between Sj&ouml, gren syndrome and non-Hodgkin lymphoma, mostly extranodal marginal zone lymphomas and, less often, diffuse large B-cell, is well established, many other variables, such as time of onset, gender predilection, sites of occurrence, subtype of lymphoma, and predictive factors, still remain unclear. We report on a rare case of primary breast lymphoma occurring three years after the diagnosis of Sj&ouml, gren syndrome in a 57-year-old patient. The diagnostic work-up, including radiograms, core needle biopsy, and histological examination, is discussed, along with emerging data from the recent literature, thus highlighting the usefulness of breast surveillance in Sj&ouml, gren syndrome patients.

Contrast-Enhanced Spectral Mammography (CESM) is a recently introduced mammographic method with characteristics particularly suitable for breast cancer radiomic analysis. This work aims to evaluate radiomic features for predicting histological outcome and two cancer molecular subtypes, namely Human Epidermal growth factor Receptor 2 (HER2)-positive and triple-negative. From 52 patients, 68 lesions were identified and confirmed on histological examination. Radiomic analysis was performed on regions of interest (ROIs) selected from both low-energy (LE) and ReCombined (RC) CESM images. Fourteen statistical features were extracted from each ROI. Expression of estrogen receptor (ER) was significantly correlated with variation coefficient and variation range calculated on both LE and RC images; progesterone receptor (PR) with skewness index calculated on LE images; and Ki67 with variation coefficient, variation range, entropy and relative smoothness indices calculated on RC images. HER2 was significantly associated with relative smoothness calculated on LE images, and grading tumor with variation coefficient, entropy and relative smoothness calculated on RC images. Encouraging results for differentiation between ER+/ER−, PR+/PR−, HER2+/HER2−, Ki67+/Ki67−, High-Grade/Low-Grade and TN/NTN were obtained. Specifically, the highest performances were obtained for discriminating HER2+/HER2− (90.87%), ER+/ER− (83.79%) and Ki67+/Ki67− (84.80%). Our results suggest an interesting role for radiomics in CESM to predict histological outcomes and particular tumors’ molecular subtype.

Rationale: Anaplastic large T-cell lymphoma (BI-ALCL) is a rare primitive lymphoma described in women with breast implant prostheses, which has been arousing interest in recent years due to its potentially high social impact. The difficult diagnosis associated with the high and increasing number of prosthetic implants worldwide has led to hypothesize an underestimation of the real impact of the disease among prosthesis-bearing women. The aim of this work is to search for specific radiological signs of disease linked to the chronic inflammatory pathogenetic mechanism. Patient concerns: This work describes a case of BI-ALCL in an American woman with no personal or family history of cancer, who underwent breast augmentation for esthetic purposes at our Institute. After about 10 years of relative well-being, the patient returned to our Institute with clear evidence of breast asymmetry due to the increase in volume of the right breast which had progressively become larger over a period of 6 months. There was no evidence of palpable axillary lymph nodes or other noteworthy signs. Diagnosis: The ultrasound and magnetic resonance (MR) tests indicated the presence of seroma with amorphous material in the exudate which was confirmed by indirect signs, visible in right breast mammography. Due to suspected cold seroma, an ultrasound-guided needle aspiration was performed for the cytological analysis of the effusion which highlighted the presence of a number of large-sized atypical cells with an irregular nucleus with CD30 immunoreactivity, leucocyte common antigen (CD45) compatible with the BI-ALCL diagnosis. Interventions: In our case, a capsulectomy was performed because the disease was limited inside the capsule and periprosthetic seroma. The final histological examination confirmed the stage. Lessons: The patient is being monitored and shows no signs of recurrence of disease >24 months after surgery. Conclusion: A diagnosis of BI-ALCL can be reached using new radiological indicators, such as fibrin, which is clearly visible by MR in the form of nonvascularized debris of amorphous material hypointense in all sequences, free flowing or adhered to the external surface of the prosthesis.

Background The therapeutic approach of gastric cancer strictly depends on TNM staging mainly provided by CT and PET/CT. However, the lymph node size criterion as detected by MDCT causes a poor differential diagnosis between reactive and metastatic enlarged lymph nodes with low specificity values. Our study aims to compare 320-row CT Net enhancement and fluorine-18 fluoro-2-deoxy-d-glucose positron emission tomography/computed tomography (F-FDG PET/CT) SUV for N staging of gastric cancer. Materials and methods 45 patients with histologically proven gastric cancer underwent CT and F-FDG PET/CT. Two radiologists in consensus evaluated all images and calculated the CT Net enhancement and F-FDG PET/CT SUV for N staging, having the histological findings as the reference standard. CT and F-FDG PET/CT sensitivity, specificity, diagnostic accuracy, positive and negative predictive values (PPV and NPV) were evaluated and compared by using the Mc Nemar test. Results The histological examination revealed nodal metastases in 29/45 cases (64%). CT Net enhancement obtained sensitivity, specificity, accuracy, PPV and NPV of 90%, 81%, 87%, 90% and 81%, respectively. F-FDG PET/CT SUV obtained sensitivity, specificity, accuracy, PPV and NPV of 66%, 88%, 73%, 90% and 58%, respectively. No statistically significant difference between the two imaging modalities was found (p = 0.1). Conclusion CT Net enhancement represents an accurate tool for N staging of gastric cancer and could be considered as the CT corresponding quantitative parameter of F-FDG PET/CT SUV. It could be applied in the clinical practice for differentiating reactive lymph nodes from metastatic ones improving accuracy and specificity of CT., Highlights • Gastric cancer N staging represents a diagnostic challenge for patient management. • CT and PET-TC play a crucial role in this field. • CT has a high sensitivity and a low specificity. • Disease over-staging causes ineffective care when patient categorized as palliative is excluded from curative treatment. • The proposed new 3D CT software with quantitative data for N staging improves CT specificity.

Preoperative staging is crucial for oral cancer management. The purpose of this study was to assess the tumor thickness using ultrasound and to correlate the level of histological infiltration with the tumor superficial extension and lesion thickness.Thirty-two subjects affected by oral cavity carcinoma were prospectively evaluated with intraoral ultrasound. The ultrasound sensitivity, the correlation between the ultrasound level of infiltration, and lesion diameters and thickness were assessed.A 91% ultrasound sensitivity was found with no significant correlation between tumor diameter and level of histological infiltration (P.05). A thickness of2 mm was associated to tumor extension to the lamina propria, a value of6 mm to muscular layer infiltration. Lymph adenopathies were identified in 21% of cases, associated to muscular layer infiltration in all cases.In the study of early oral cavity tumors, ultrasound is accurate for demonstrating the level of tumor infiltration and contributes to the therapeutic choice.

Background Our aim was to compare the diagnostic performance of digital breast tomosynthesis (DBT)-galactography with that of full-field digital (FFD)-galactography for detecting intraductal breast lesions using an intra-individual design. Methods Forty-nine consecutive patients with spontaneous, unilateral, single-pore nipple discharge and inconclusive FFD mammography and ultrasonography underwent galactography with a “COMBO” technique combining FFD- and DBT-galactography acquisitions. Examinations were independently analysed by two breast radiologists with 10-year experience. Sensitivity, specificity, and accuracy for both FFD- and DBT-galactography were calculated having histological examinations of surgical specimens as a reference standard. Data were presented as percentages with their 95% confidence intervals (CI). McNemar test was used. Interobserver agreement was assessed by using Cohen κ test for both techniques. Results Sensitivity was 41/43 (95%, 95% CI 84.2–99.4) for DBT-galactography and 33/43 (77%, 95% CI 61.4–88.2) for FFD-galactography (p = 0.008), specificity 6/6 (100%, 95% CI 54.1–100.0) for both imaging tools, accuracy 47/49 (96%, 95% CI 86.0–99.5) and 39/49 (80%, 95% CI 65.7–89.8) (p = 0.038), respectively. The inter-observer agreement was 0.86 for DBT-galactography and 0.78 for FFD-galactography. The AGD resulted to 1.94 ± 0.64 for the combined technique. Conclusion DBT-galactography showed a significantly higher sensitivity and accuracy than FFD-galactography for the identification of the intraductal findings, improving the possibility of a reliable diagnosis in patients with pathologic nipple-discharge.

BackgroundThe automatic segmentation of kidneys in medical images is not a trivial task when the subjects undergoing the medical examination are affected by Autosomal Dominant Polycystic Kidney Disease (ADPKD). Several works dealing with the segmentation of Computed Tomography images from pathological subjects were proposed, showing high invasiveness of the examination or requiring interaction by the user for performing the segmentation of the images. In this work, we propose a fully-automated approach for the segmentation of Magnetic Resonance images, both reducing the invasiveness of the acquisition device and not requiring any interaction by the users for the segmentation of the images.MethodsTwo different approaches are proposed based on Deep Learning architectures using Convolutional Neural Networks (CNN) for the semantic segmentation of images, without needing to extract any hand-crafted features. In details, the first approach performs the automatic segmentation of images without any procedure for pre-processing the input. Conversely, the second approach performs a two-steps classification strategy: a first CNN automatically detects Regions Of Interest (ROIs); a subsequent classifier performs the semantic segmentation on the ROIs previously extracted.ResultsResults show that even though the detection of ROIs shows an overall high number of false positives, the subsequent semantic segmentation on the extracted ROIs allows achieving high performance in terms of mean Accuracy. However, the segmentation of the entire images input to the network remains the most accurate and reliable approach showing better performance than the previous approach.ConclusionThe obtained results show that both the investigated approaches are reliable for the semantic segmentation of polycystic kidneys since both the strategies reach an Accuracy higher than 85%. Also, both the investigated methodologies show performances comparable and consistent with other approaches found in literature working on images from different sources, reducing both the invasiveness of the analyses and the interaction needed by the users for performing the segmentation task.

Multi-detector computed tomography (MDCT) represents the gold standard in patients with acute abdomen syndrome and suspected bowel ischemia. It provides a correct diagnosis and contributes to appropriate treatment planning. This study aims to evaluate the role of 3D Tissue Transition Projection (TTP) transparent wall CT reconstruction for detecting the degree of bowel dilatation and to correlate this finding with the aetiology and prognosis in patients affected by mesenteric infarction.Forty-seven patients affected by bowel infarction due to vascular obstruction (arterial in 66% of cases, venous in 34%) were assessed by MDCT examination searching for the degree of bowel dilatation (subdivided into 4 groups: entire small bowel (SB); ≥50% of SB;50% of SB; large bowel only). Two blinded radiologists evaluated TTP 3D transparent wall and multi-planar reconstructions. Chi square test was used to correlate CT findings with the disease course and the mortality rate. Cohen's kappa statistics was used in order to assess inter-observer agreement.The overall mortality rate was 64%, with a 90% value for arterial forms and 10% in case of venous infarctions. The entire SB (n = 10) or a ≥50% SB dilatation (n = 16) correlated with poor prognosis in all cases (p 0.05); a50% SB dilatation (n = 16) correlated with good prognosis in 87.5% of cases (p 0.05). A large bowel only dilatation (n = 5) did not show a significant prognostic value (p = 0.13). Almost perfect agreement between the two readers was found (k = 0.84).MDCT offers different reconstruction software for diagnosing bowel ischemia. 3D TTP transparent wall reconstructions represent a rapid and automatic tool for identifying loop dilatation, which significantly correlates with an arterial aetiology and poor prognosis.

Despite several studies having identified factors associated with successful treatment outcomes in locally advanced cervical cancer, there is the lack of accurate predictive modeling for progression-free survival (PFS) in patients who undergo radical hysterectomy after neoadjuvant chemotherapy (NACT). Here we investigated whether machine learning (ML) may have the potential to provide a tool to predict neoadjuvant treatment response as PFS. In this retrospective observational study, we analyzed patients with locally advanced cervical cancer (FIGO stages IB2, IB3, IIA1, IIA2, IIB, and IIIC1) who were followed in a tertiary center from 2010 to 2018. Demographic and clinical characteristics were collected at either treatment baseline or at 24-month follow-up. Furthermore, we recorded data about magnetic resonance imaging (MRI) examinations and post-surgery histopathology. Proper feature selection was used to determine an attribute core set. Three different machine learning algorithms, namely Logistic Regression (LR), Random Forest (RFF), and K-nearest neighbors (KNN), were then trained and validated with 10-fold cross-validation to predict 24-month PFS. Our analysis included n. 92 patients. The attribute core set used to train machine learning algorithms included the presence/absence of fornix infiltration at pre-treatment MRI as well as of either parametrium invasion and lymph nodes involvement at post-surgery histopathology. RFF showed the best performance (accuracy 82.4%, precision 83.4%, recall 96.2%, area under receiver operating characteristic curve (AUROC) 0.82). We developed an accurate ML model to predict 24-month PFS.

Background Microcalcification clusters in mammograms can be considered as early signs of breast cancer. However, their detection is a very challenging task because of different factors: large variety of breast composition, highly textured breast anatomy, impalpable size of microcalcifications in some cases, as well as inherent low contrast of mammograms. Thus, the need to support the clinicians’ work with an automatic tool. Methods In this work a three-phases approach for clustered microcalcification detection is presented. Specifically, it is made up of a pre-processing step, aimed at highlighting potentially interesting breast structures, followed by a single microcalcification detection step, based on Hough transform, that is able to grasp the innate characteristic shape of the structures of interest. Finally, a cluster identification step to group microcalcifications is carried out by means of a clustering algorithm able to codify expert domain rules. Results The detection performance of the proposed method has been evaluated on 364 mammograms of 182 patients obtaining a true positive ratio of 91.78 % with 2.87 false positives per image. Conclusions Experimental results demonstrated that the proposed method is able to detect microcalcification clusters in digital mammograms showing performance comparable to different methodologies exploited in the state-of-art approaches, with the advantage that it does not require any training phase and a large set of data. The performance of the proposed approach remains high even for more difficult clinical cases of mammograms of young women having high-density breast tissue thus resulting in a reduced contrast between microcalcifications and surrounding dense tissues.

Computer Aided Decision (CAD) systems, based on 3D tomosynthesis imaging, could support radiologists in classifying different kinds of breast lesions and then improve the diagnosis of breast cancer (BC) with a lower X-ray dose than in Computer Tomography (CT) systems. In previous work, several Convolutional Neural Network (CNN) architectures were evaluated to discriminate four different classes of lesions considering high-resolution images automatically segmented: (a) irregular opacity lesions, (b) regular opacity lesions, (c) stellar opacity lesions and (d) no-lesions. In this paper, instead, we use the same previously extracted relevant Regions of Interest (ROIs) containing the lesions, but we propose and evaluate two different approaches to better discriminate among the four classes. In this work, we evaluate and compare the performance of two different frameworks both considering supervised classifiers topologies. The first framework is feature-based, and consider morphological and textural hand-crafted features, extracted from each ROI, as input to optimised Artificial Neural Network (ANN) classifiers. The second framework, instead, considers non-neural classifiers based on automatically computed features evaluating the classification performance extracting several sets of features using different Convolutional Neural Network models. Final results show that the second framework, based on features computed automatically by CNN architectures performs better than the first approach, in terms of accuracy, specificity, and sensitivity.

The segmentation of kidneys from Magnetic Resonance (MR) images of subjects affected by Autosomal Dominant Polycystic Kidney Disease (ADPKD) is a task of fundamental importance as it allows a non-invasive assessment and monitoring of the disease over time. In this work, a fully automated procedure based on Convolutional Neural Networks (CNNs) is proposed for detecting images containing the kidney and subsequently segment them classifying each pixel. Specifically, a mono-objective genetic algorithm was designed for optimising the CNN architecture, modelling the number of encoders, the structure of each encoder and the final fully-connected layers. The input dataset for the classification task included 526 MR images: 366 containing kidney and 160 did not include any pixel of the kidney. All the images containing the kidney were split into left and right side and used as input dataset for the segmentation procedure. For both the tasks, the training set, validation set and test set were generated according to the 60-20-20 percentages. Accuracy higher than 95% for the classification task and 90% for the segmentation algorithm show the reliability of the proposed approach, also improving the results of previous works.

Purpose To evaluate the distribution of MRI breast parenchymal enhancement (BPE) among different breast cancer subtypes searching for any significant difference in terms of immunohistochemical and receptorial patterns (Estrogen Receptor -ER, Progesterone Receptor - PR, Human Epidermal Growth Factor Receptor 2 - HER2). Methods 82 consecutive patients affected by breast cancer underwent breast DCE-MRI. Two radiologists retrospectively evaluated all subtracted MR enhanced images for classifying BPE. ER, PR and HER2 expression was assessed by immunohistochemical analysis. ER and PR status was evaluated using Allred score (positive values: score ≥3). The intensity of the cerbB-2 staining was scored as 0, 1+, 2+, or 3+ (positive values: ≥ 3+; negative:0 and 1+; 2+ value assessed with silver in-situ hybridization). Patients were classified into five categories based on cancer subtypes: Luminal A, Luminal B HER2 negative, Luminal B HER2 positive, HER2 positive non luminal, triple negative. The χ2 test was used for evaluating the significance of BPE type distribution into the five groups of tumor subtypes and the distribution of the five breast cancer subtypes among every single BPE type. The correlation of BPE with factors such as age, menopausal status and lesion diameter was investigated using multivariate regression analysis and logistic regression. Cohen's kappa statistics was used in order to assess inter-observer agreement for classifying BPE. Results 6/82 cases were Luminal A-like (7.3%), 42/82 Luminal B-like (HER2-) (51.2%), 12/82 Luminal B-like (HER2+) (14.6%), 4/82 Non Luminal (HER+) (4.9%), 18/82 Triple Negative (ductal) (22%). 16/82 cases showed minimal BPE, 28/82 mild BPE, 22/82 moderate BPE, 16/82 marked BPE. Mild BPE pattern was significantly more prevalent (p = 0.0001) than other BPE types only in the luminal B (HER-) tumors. Moderate and marked BPE prevailed over minimal and mild, in triple negatives. Among all patients with mild BPE, luminal B (HER2-) tumors were significantly higher (p = 0.0001). Among all patients with marked BPE, triple negative subtypes were significantly higher (p = 0.0074). No significant confounder to BPE qualitative evaluation was found (p = 0.39). The inter-rater agreement in evaluating BPE patterns on MRI was almost perfect with Cohen’s k = 0.83. Conclusions BPE could play a crucial role as an imaging bridge to molecular breast cancer subtype allowing an additional risk stratification in the field of breast MRI and targeted screening tests. Luminal B (HER2-) tumors could prevail in case of mild BPE on CE-MRI examinations and TN tumors in patients with marked BPE. Further studies on larger series are needed to confirm this hypothesis.

We read with interest the results of the retrospective study by Hadjinicolaou et al . (1) which described a case of primary small bowel malignant melanoma (SBM) in a 60-year-old man with review of the literature. The authors conclude that primary SBM is a rare entity, affect more frequently the men, with debatable pathophysiology.

Adenocarcinoma of the ceruminous glands is a rare malignancy arising from the glands of the external auditory canal. In most patients it is usually diagnosed as locally advanced disease with a major obstacle for radical surgery.

To investigate whether background parenchymal enhancement (BPE) and breast cancer would correlate searching for any significant difference of BPE pattern distribution in case of benign or malignant lesions.386 patients, including 180 pre-menopausal (group 1) and 206 post-menopausal (group 2), underwent MR examination. Two radiologists evaluated MR images classifying normal BPE as minimal, mild, moderate or marked. The two groups of patients were subdivided into 3 categories based on MRI findings (negative, benign and malignant lesions). The distribution of BPE patterns within the two groups and within the three MR categories was calculated. The χ2 test was used to evaluate BPE type distribution in the three patient categories and any statistically significant correlation of BPE with lesion type was calculated. The Student t test was applied to search for any statistically significant difference between BPE type rates in group 1 and 2.The χ2 test demonstrated a statistically significant difference in the distribution of BPE types in negative patients and benign lesions as compared with malignant ones (p0.05). A significantly higher prevalence of moderate and marked BPE was found among malignant lesions (group 1: 32% and 42%, respectively; group 2: 31% and 46%, respectively) while a predominance of minimal and mild BPE among negative patients (group 1: 60% and 36%, respectively; group 2: 68% and 32%, respectively) and benign lesions (group 1: 54% and 38%, respectively; group 2: 75% and 17%, respectively) was found. The Student t test did not show a statistically significant difference between BPE type rates in group 1 and 2 (p0.05).Normal BPE could correlate with the risk of breast cancer being such BPE patterns as moderate and marked associated with patients with malignant lesions in both pre and post-menopausal women.

Purpose: To evaluate the role of multidetector computed tomography (MDCT) in recognizing the complications of extracorporeal shock wave lithotripsy (ESWL) and providing a prognostic grading system for the therapeutic approach. Materials and Methods: A total of 43 patients who underwent ESWL because of urinary stone disease were assessed by 320-row MDCT examination before and after ESWL. Pre-ESWL CT unenhanced scans were performed for diagnosing stone disease. Post-ESWL CT scans were acquired before and after intravenous injection of contrast medium searching for peri-renal fluid collection or hyper-density, pyelic or ureteral wall thickening, blood clots in the urinary tract, peri- or intra-renal hematoma or abscess, active bleeding. A severity grading system of ESWL complications was established. Results: Patients were affected by renal (n = 36) or ureteral (n = 7) lithiasis. Post-ESWL CT examination detected small fluid collections and hyper-density of peri-renal fat tissue in 35/43 patients (81%), pyelic or ureteral wall thickening in 2/43 (4%), blood clots in the urinary tract in 9/43 (21%), renal abscesses or hematomas with a diameter of

Purpose To assess the role of STIR, T2-weighted TSE and DWIBS sequences for detecting and characterizing breast lesions and to compare unenhanced (UE)-MRI results with contrast-enhanced (CE)-MRI and histological findings, having the latter as the reference standard. Materials and Methods Two hundred eighty consecutive patients (age range, 27–73 years; mean age ± standard deviation (SD), 48.8 ± 9.8 years) underwent MR examination with a diagnostic protocol including STIR, T2-weighted TSE, THRIVE and DWIBS sequences. Two radiologists blinded to both dynamic sequences and histological findings evaluated in consensus STIR, T2-weighted TSE and DWIBS sequences and after two weeks CE-MRI images searching for breast lesions. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy for UE-MRI and CE-MRI were calculated. UE-MRI results were also compared with CE- MRI. Results UE-MRI sequences obtained sensitivity, specificity, diagnostic accuracy, PPV and NPV values of 94%, 79%, 86%, 79% and 94%, respectively. CE-MRI sequences obtained sensitivity, specificity, diagnostic accuracy, PPV and NPV values of 98%, 83%, 90%, 84% and 98%, respectively. No statistically significant difference between UE-MRI and CE-MRI was found. Conclusion Breast UE-MRI could represent an accurate diagnostic tool and a valid alternative to CE-MRI for evaluating breast lesions. STIR and DWIBS sequences allow to detect breast lesions while T2-weighted TSE sequences and ADC values could be useful for lesion characterization.

To assess the diagnostic accuracy and inter-observer variability of ultrasound (US) in recognizing signs of intra or extra-capsular rupture of silicone breast implants by using the magnetic resonance imaging (MRI) findings as the reference standard.150 patients for a total of 300 implants underwent breast US and subsequently MR examination searching for signs of intra or extra-capsular rupture. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy were calculated for breast US having MRI findings as the reference standard. Cohen's kappa statistics was used in order to assess inter-observer agreement for US.170/300 (57 %) implant ruptures were detected at US (intra-capsular n = 110, extra-capsular n = 60). By comparing US findings with MR results, overall sensitivity, specificity, accuracy, PPV, and NPV of 79, 63, 70, 65, and 77 %, respectively, were found for breast US. In case of intra-capsular rupture, sensitivity, specificity, accuracy, PPV, and NPV of 63, 63, 63, 45, and 77 %, respectively, were obtained; 100 % values were found for extra-capsular rupture US diagnosis.US can be used as the first examination in patients with breast implants. US intra-capsular rupture detection requires further evaluation by MRI; in case of extra-capsular rupture US diagnosis, surgical implant removal could be proposed without further investigations.valutare l’accuratezza diagnostica e la variabilità inter-osservatore dell’ecografia nel riconoscimento dei segni di rottura intra od extra-capsulare di protesi mammarie in silicone avendo i segni RM con standard di riferimento.150 pazienti per un totale di 300 impianti sono stati sottoposti ad ecografia mammaria e successivamente ad esame RM ricercando segni di rottura intra od extracapsulare. Sono stati calcolati i valori di sensibilità, specificità, valori predittivi positivo (VPP) e negativo (VPN) ed accuratezza diagnostica avendo i segni RM come standard di riferimento. L’accordo inter-osservatore è stato calcolato mediante test statistico kappa di Cohen.170/300 (57 %) rotture di impianti sono state identificate all’esame ecografico (intra-capsulari,l’ecografia mammaria può essere utilizzata come metodica di primo livello nei pazienti con protesi mammarie. In caso di diagnosi ecografica di rottura intra-capsulare, è indicato approfondimento diagnostico con esame RM; in caso di rottura extra-capsulare rilevata all’esame ecografico, è proponibile la sostituzione chirurgica dell’impianto senza ulteriori indagini diagnostiche.

Acute adrenal ischemia represents a rare cause of adrenal insufficiency which should be promptly diagnosed in order to preserve adrenal vitality and function. Our study aims to retrospectively evaluate the diagnostic accuracy of the CT capsular sign as an indicator of adrenal ischemia and its association with vascular involvement. Between January 2013 and January 2014, 69 consecutive patients (47 men, 22 women; mean age 46; range 22-67) with suspected adrenal insufficiency based on clinical and biochemical data underwent 320-row CT examination in our Emergency Department. Written informed consent was obtained for the CT examinations, and the institutional review board approval was obtained for our retrospective study. CT multi-planar images were retrospectively and independently analyzed by two radiologists searching for the patency of adrenal vessels, enlarged adrenals, the presence of the "capsular sign" represented by a peripheral subtle hyperdense line around a hypodense enlarged adrenal, and the presence of any periadrenal inflammatory changes. All CT findings were then compared with the surgical findings (n = 5), follow-up examinations (n = 20), or autopsy (n = 4). Sensitivity, specificity, diagnostic accuracy (DA), positive predictive value (PPV), and negative predictive value (NPV) were calculated for the "capsular sign" and were further evaluated by ROC analysis. Acute adrenal ischemia occurred in 29/69 patients (42 %), unilateral in 20, and bilateral in 9. Forty of sixty-nine patients (58 %) had no evidence of adrenal disease on CT. Thrombosis of the main adrenal vein was found in 20/29 (69 %) and non-venous ischemia in 9/29 (31 %). The capsular sign was found in 24/29 patients (83 %). Sensitivity, specificity, DA, PPV, and NPV values of 83, 100, 93, 100, and 89 %, respectively, were obtained. The capsular sign represents a CT indicator of acute adrenal ischemia, with a specificity of 100 % and leading to a prompt diagnosis in the early phase of the disease.

The automatic segmentation of kidneys in medical images is not a trivial task when the subjects undergoing the medical examination are affected by Autosomal Dominant Polycystic Kidney Disease.

Screening programs use mammography as primary diagnostic tool for detecting breast cancer at an early stage. The diagnosis of some lesions, such as microcalcifications, is still difficult today for radiologists. In this paper, we proposed an automatic model for characterizing and discriminating tissue in normal/abnormal and benign/malign in digital mammograms, as support tool for the radiologists. We trained a Random Forest classifier on some textural features extracted on a multiscale image decomposition based on the Haar wavelet transform combined with the interest points and corners detected by using Speeded Up Robust Feature (SURF) and Minimum Eigenvalue Algorithm (MinEigenAlg), respectively. We tested the proposed model on 192 ROIs extracted from 176 digital mammograms of a public database. The model proposed was high performing in the prediction of the normal/abnormal and benign/malignant ROIs, with a median AUC value of \(98.46\%\) and \(94.19\%\), respectively. The experimental result was comparable with related work performance.

Objectives. To assess the potential of CT for characterizing small renal tumors.Methods. 76 patients with Results. Calcifications were found in 7/56 (12.5%) carcinomas. Clear cell carcinomas were as follows: mean density 183.5 HU (arterial phase), 136 HU (portal phase), and 94 HU (delayed phase), washout 34.3%; chromophobe carcinomas were as follows: mean density 135 HU (arterial phase), 161 HU (portal phase), and 148 HU (delayed phase), washout 28%; papillary carcinomas were as follows: mean density 50.3 HU (arterial phase), 60 HU (portal phase), and 58.1 HU (delayed phase), washout 2.7%. In 2/56 (3.6%) cases urinary tract infiltration was found. Oncocytomas were as follows: mean density 126.5 HU (arterial phase), 147.5 HU (portal phase), and 115.5 HU (delayed phase), washout 28.6%. On unenhanced scans, angiomyolipomas were as follows: density values Conclusions. Intralesional calcifications and urinary tract infiltration are suggestive for malignancy, with the evidence of adipose tissue for angiomyolipomas and a modest increase in density with a reduced washout for papillary carcinomas. The intralesional density on enhanced scans, peak enhancement, and washout do not seem significant for differentiating clear cell, chromophobe carcinomas, angiomyolipomas, and oncocytomas.

Pneumatosis cystoides intestinalis (PCI) is a rare disease characterized by the presence of multiple gas-filled cysts within the submucosa or subserosa of the intestinal wall. We report a case of PCI in a 54-year-old man 4 weeks after liver transplantation due to hepatitis B virus (HBV)-associated liver cirrhosis presenting with illness, diarrhea and abdominal pain. CT scans revealed normal shape of the abdominal parenchymal organs and no intra-hepatic complication due to liver transplantation. Main abdominal venous and arterial vessels resulted patent. Colic loops appeared diffusely thickened for the presence of variable diameter air-filled cysts located within the bowel wall. The patient underwent conservative treatment and the CT control after 4 weeks showed a complete PCI resolution. PCI after adult liver transplantation is probably due to the pre-transplantation chemotherapy, immunosuppressive therapy and opportunistic enteric infections. Abdominal CT represents the gold standard technique for diagnosing PCI and for evaluating its extension and complications providing data on other abdominal pathologies. It appears as variable diameter gas-filled cysts located within the bowel wall and it is often associated with pneumo-peritoneum probably due to the rupture of subserosal cysts. PCI has a favorable outcome and requires conservative treatment. Major differential diagnosis includes intestinal pneumatosis due to bowel ischemia. PCI after liver transplantation represents an uncommon bowel disease with a favorable prognosis. CT represents the reference imaging technique for diagnosing the disease and evaluating the response to therapy which is usually conservative rather than surgical.

Purpose Our purpose was to retrospectively evaluate the incidence and morphologic features of diabetic mastopathy in a group of patients with diabetes, searching for specific sonographic characteristics of diabetic mastopathy. Methods One hundred twenty diabetic patients underwent breast clinical examination, mammography, and sonography. All detected breast lesions were confirmed histopathologically. Results Breast lesions were found in 11 of the 120 patients (9%), including two cases of invasive ductal carcinomas and nine cases of diabetic mastopathy. In seven of those nine cases (77%), diabetic mastopathy appeared as a hypoechoic solid mass with irregular margins, inhomogeneous echotexture, and marked posterior shadowing. In the other two cases (23%), it appeared as a mildly inhomogeneous, hypoechoic solid mass. Conclusions Diabetic mastopathy is a diagnostic challenge and needs to be suspected in all patients with diabetes mellitus. Imaging features are nonspecific and highly susggestive on breast sonography in most cases. Core-needle biopsy confirmation remains mandatory for a definitive diagnosis. © 2014 Wiley Periodicals, Inc. J Clin Ultrasound, 43:113–117, 2015

Purpose Mammography is the most effective and low-cost method for the early detection of breast cancers. The aim of this study was to develop an automated model in order to improve detection and characterization of clustered microcalcifications on full-field digital mammograms (FFDM). Methods We analyzed 98 digital mammograms extracted from the public database Breast Cancer Digital Repository with 276 microcalcification clusters; these images were previously evaluated in double blind by two radiologists which had identified the microcalcification clusters. We identified some regions of interest (ROI) on mammograms after pre-processing by using the Circular Hough Transform algorithm in order to recognize circles corresponding to the microcalcifications. Then, we selected morphological and morphometric features for each ROI, such as Speeded Up Robust Feature, as well as classic statistical features based on Haar Transform. These features were used for giving instructions to a Random Forest classifier in order to recognize – riga clustered microcalcifications normal and abnormal ROIs. Finally, we tested the performance of – riga this automated model in cross-validation and with statistical measurements. Results Statistical results ( Table 1 ) showed good performance of proposed model in automatic detection of breast clustered microcalcifications on FFDM (sensitivity over 90% with 3.54 false positives – riga per image), even in young patients with dense breast tissue (sensitivity over 88%) and according to published data [1] . Also classification performance of clustered microcalcifications (AUC 98,6 ± 0,1, Accuracy 97,6 ± 0,2%, Sensitivity 97,7 ± 0,4%, Specificity 96,2 ± 0,4%) was comparable with the state of the art [2] . Conclusions The proposed automated model enables to improve detection of clustered microcalcifications that could be characterized by difficult diagnostic interpretation especially when occurred in dense breast parenchyma. The proposed model results highly performing and comparable to the state-of-art approaches.

In this paper, we propose a deep learning approach for breast lesions classification, by processing breast images obtained using an innovative acquisition system, the Tomosynthesis, a medical instrument able to acquire high-resolution images using a lower radiographic dose than normal Computed Tomography (CT). The acquired images were processed to obtain Regions Of Interest (ROIs) containing lesions of different categories. Subsequently, several pre-trained Convolutional Neural Network (CNN) models were evaluated as feature extractors and coupled with non-neural classifiers for discriminate among the different categories of lesions. Results showed that the use of CNNs as feature extractor and the subsequent classification using a non-neural classifier reaches high values of Accuracy, Sensitivity and Specificity.

Introduction and objective: Computer Aided Decision (CAD) systems based on Medical Imaging could support radiologists in classifying malignant regions from benign ones, in the field of investigation for breast cancer detection. This decision may often follow a previous procedure dedicated to the earlier identification of Regions Of Interest (ROI) containing still unclassified lesions. Materials and methods: Materials comprise features extracted from magnetic resonance (MR) images representing morphological properties of lesions. The Regions Of Interest identified by a previous automatic procedure validated by radiologists of the University of Bari Aldo Moro (Italy), authors of this work, 134 from 600 slices considered of interest, because they contain still unclassified damaged areas. Several techniques were tested for ROI segmentation and classification. In particular, it can be shown that the same procedures for lesioned-area discrimination were also useful for malignancy classification of lesions, themselves. In particular, MR images were processed with different image processing techniques for ROI extraction, which were, ultimately, described by morphological features, such as circularity, aspect ratio, solidity and convexity. Finally, we discuss a procedure to design a feed-forward supervised artificial neural networks (ANN) architecture based on an evolutionary strategy. In a similar approach, different ANN topologies were tested in order to find the best in terms of mean accuracy for several iterations of training, validation and test. In particular, for each topology, the training, validation and test sets were constructed using 100 random permutations of the dataset, from which the average performances were calculated. Results: The performance of the best ANN architecture, trained using a training set of 82 samples (equally divided between malignant and benign lesions) from the 134 samples available in the whole dataset, were evaluated in terms of accuracy, sensitivity and specificity. Conclusion: Testing determined that the supervised ANN approach is consistent and reveals good performance; in particular, the optimal ANN topology found through an evolutionary strategy showed high generalization on the mean performance indexes regardless of training, validation and test sets applied, showing good performances in terms of both accuracy and sensitivity, permitting correct classification of the true malignant lesions.

Iodine-131 ((131)I) total-body scintigraphy is a commonly used post-thyroidectomy imaging procedure in the management of differentiated thyroid cancer (DTC), in particular in patients with an intermediate or high risk of persistent or recurrent disease, in combination with serum thyroglobulin (Tg) determinations and ultrasonography of the neck. It can show the persistence of residual thyroid tissue after thyroidectomy and local and distant metastases. Although this is a highly sensitive method for detecting normal and pathologic thyroid tissue, especially when performed after an ablative dose of (131)I, false-positive scans (i.e., uptake in the absence of residual thyroid tissue or metastases) can occur in different situations.We report a case of a 42-year-old woman with recurrent chest infections and bronchiectasis, who had a total thyroidectomy and (131)I treatment because of a papillary thyroid carcinoma. She presented with marked bilateral (131)I uptake in the lungs mimicking metastatic involvement of the lungs by thyroid cancer, but interpreted as nonspecific bilateral uptake by her bronchiectatic bronchial tree.Our case, as well as others reported in the literature, calls attention to the fact that (131)I lung uptake may be related to chronic inflammatory lung disease, thus representing a potential diagnostic pitfall in patients with DTC.(131)I uptake should be interpreted on the bases of clinical context, imaging, and laboratory findings (serum Tg). Recognition of potential false-positive (131)I scans is critical to avoid unnecessary exposure to further radiation from repeated therapeutic doses of (131)I with possible side effects and even worsening of lung disease itself.

Objectives: To evaluate the primary lesions, the complications and the evolution of disease in patients affected by H1N1 viral infection. Materials and Methods: 24 Patients affected by H1N1 infection, diagnosed by polymerase chain reaction (PCR) on throat swabs, underwent CT examination. Seven patients were hospitalized in intensive care unit (ICU). In five patients the evolution of disease was monitored. The following features were evaluated: primary lesions significant for viral infection, their possible complications and the evolution of disease in controlled patients. Results: Primary lesions variously associated with each other were found in 22 out of 24 patients: ground glass opacities (19/24, 79.2%), interstitial thickening (13/24, 54.2%), centrilobular nodules (3/24, 12.5%) and consolidation (8/24, 33.3%). The following complications were observed: 3 consolidations with air bronchogram, 9 pleural effusions, 7 ARDS and 1 barotrauma. In the 5 patients who underwent follow-up (including 3 admitted to ICU), complete resolution was demonstrated in 4 cases and focal fibrotic evolution in one case. 3 ICU patients affected by ARDS died. Conclusions: In case of H1N1 virus infection. CT is an important tool for staging the disease, recognize complications and to study disease evolution

Purpose Dual-energy contrast-enhanced spectral mammography (CESM) has emerged as a potential new option for breast cancer staging. This imaging technique allows acquisition of multiple views of both breasts after a single injection of iodinated Contrast Medium (CM). It based on the fact that the CM injected will have different uptake path between hypervascularized breast lesions and background parenchyma. The aim of this paper is to evaluate the performance of identifying and characterizing the breast lesions, costs and comfort of patients of a supervision CESM single-step path with respect to a traditional double-step path mammography and MRI. Methods We collected data on 46 patients who performed CESM: we have selected a subsample that also performed mammography in tomosynthesis and MRI. A total of 33 lesions have been identified by histological examination (28 malignant and 5 benign). The findings of all the techniques have been submitted to double blind check by two radiologists. The test was performed on 2D synthetic images of tomosynthesis and confirmed in low-energy images of CESM as reported in literature [1] . We have performed a statistical analysis of the diagnostic performances of each method in order to estimate the efficiency of the proposed diagnostic path with the only CESM technique with respect to the traditional path. Results This study have shown consistent results in terms of sensitivity (over 90%) and between paths. The total costs of CESM alone were lower than the combination of digital mammography and MRI with CM, and between the different methods, while the greater discomfort was reported by patients undergoing MRI. Conclusions The comparison between the methods has underlined the validity of the CESM supervision model both as morphological examination with respect to traditional mammography, and as dynamic examination with respect to MRI, according to the literature. In addition, CESM is more tolerated by patients than MRI and less expensive than the traditional paths.

Purpose Contrast-Enhanced Spectral Mammography (CESM) allows the acquisition of low- and high-energy digital mammograms with Dual-Energy technique after a single injection of iodinated contrast medium (CM) obtaining the production of recombined mammographic images [1] , [2] . The aim of this paper is to characterize ROI and measure the gray-level parenchymal background in order to improve the lesion detection in CESM. Methods We have selected 42 patients positive to the methodic for the presence of at least one findings after histological examination.We have evaluated 65 lesions (52 malignant and 13 benign) from 0.5 to 13.5 cm. Primary and secondary (if present) lesions have been identified and their diameters have been measured in axial projection. Regions including the parenchymal background and the non-contrasted background were also marked in both low-energy and recombined images.For each region the statistical parameters of gray levels were recorded by CESM instrumentation and have been elaborated by multivariate statistics and machine learning techniques in order to characterize each region and define a background intensity indicator, not yet defined objectively. Results The analysis on our available dataset seems to underline significant differences between ROIs with lesions and regions marked on the parenchymal background with respect to the coefficient of variation, i.e. standard deviation of the gray levels of the marked area compared to the mean value of the same) in recombined images.We have found an increase of the coefficient of ROIs greater than 20% with respect to the coefficient of the regions marked on parenchymal background in 57 lesions. Conclusions As preliminary results, an indicator to detect the parenchymal background can be identified as the coefficient of variation. Data collection is currently ongoing because a more massive data sample will be useful to increase the sensitivity in the lesion detection by CESM device, even in patients with a medium-high value of background.

Nowadays preventive screening policies and increased awareness initiatives are up surging the workload of radiologists. Due to the growing number of women undergoing first-level screening tests, systems that can make these operations faster and more effective are required. This paper presents a Computer Assisted Detection system based on medical imaging techniques and capable of labeling potentially cancerous breast lesions. This work is based on MRIs performed with morphological and dynamic sequences, obtained and classified thanks to the collaboration of the specialists from the University of Bari Aldo Moro (Italy). A first set of 60 images was acquired without Contrast Method for each patient and, subsequently, 100 more slices were taken with Contrast Method. This article formally describes the techniques adopted to segment these images and extract the most significant features from each Region of Interest (ROI). Then, the underlying architecture of the suggested Artificial Neural Network (ANN) responsible of identifying suspect lesions will be presented. We will discuss the architecture of the supervised neural network based on the algorithm named Robust Error Back Propagation, trained and optimized so to maximize the number of True Positive ROIs, i.e., the actual tumor regions. The training set, built with physicians’ help, consists of 94 lesions and 3700 regions of any interest extracted with the proposed segmentation technique. Performances of the ANN, trained using 60 % of the samples, are evaluated in terms of accuracy, sensitivity and specificity indices. In conclusion, these tests show that a supervised machine learning approach to the detection of breast lesions in Magnetic Resonance Images is consistent, and shows good performance, especially from a False Negative reduction perspective.

The use of an abbreviated magnetic resonance (MR) protocol has been recently proposed for cancer screening. The aim of our study is to evaluate the diagnostic accuracy of an abbreviated MR protocol combining short TI inversion recovery (STIR), turbo-spin-echo (TSE)-T2 sequences, a pre-contrast T1, and a single intermediate (3 minutes after contrast injection) post-contrast T1 sequence for characterizing breast lesions.A total of 470 patients underwent breast MR examination for screening, problem solving, or preoperative staging. Two experienced radiologists evaluated both standard and abbreviated protocols in consensus. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy for both protocols were calculated (with the histological findings and 6-month ultrasound follow-up as the reference standard) and compared with the McNemar test. The post-processing and interpretation times for the MR images were compared with the paired t test.In 177 of 470 (38%) patients, the MR sequences detected 185 breast lesions. Standard and abbreviated protocols obtained sensitivity, specificity, diagnostic accuracy, PPV, and NPV values respectively of 92%, 92%, 92%, 68%, and 98% and of 89%, 91%, 91%, 64%, and 98% with no statistically significant difference (P .0001). The mean post-processing and interpretation time were, respectively, 7 ± 1 minutes and 6 ± 3.2 minutes for the standard protocol and 1 ± 1.2 minutes and 2 ± 1.2 minutes for the abbreviated protocol, with a statistically significant difference (P .01).An abbreviated combined MR protocol represents a time-saving tool for radiologists and patients with the same diagnostic potential as the standard protocol in patients undergoing breast MRI for screening, problem solving, or preoperative staging.

AIM: To evaluate the role of computed tomography (CT) for diagnosing traumatic injuries of the pancreas and guiding the therapeutic approach. METHODS: CT exams of 6740 patients admitted to our Emergency Department between May 2005 and January 2013 for abdominal trauma were retrospectively evaluated. Patients were identified through a search of our electronic archive system by using such terms as “pancreatic injury”, “pancreatic contusion”, “pancreatic laceration”, “peri-pancreatic fluid”, “pancreatic active bleeding”. All CT examinations were performed before and after the intravenous injection of contrast material using a 16-slice multidetector row computed tomography scanner. The data sets were retrospectively analyzed by two radiologists in consensus searching for specific signs of pancreatic injury (parenchymal fracture and laceration, focal or diffuse pancreatic enlargement/edema, pancreatic hematoma, active bleeding, fluid between splenic vein and pancreas) and non-specific signs (inflammatory changes in peri-pancreatic fat and mesentery, fluid surrounding the superior mesenteric artery, thickening of the left anterior renal fascia, pancreatic ductal dilatation, acute pseudocyst formation/peri-pancreatic fluid collection, fluid in the anterior and posterior pararenal spaces, fluid in transverse mesocolon and lesser sac, hemorrhage into peri-pancreatic fat, mesocolon and mesentery, extraperitoneal fluid, intra-peritoneal fluid). RESULTS: One hundred and thirty-six/Six thousand seven hundred and forty (2%) patients showed CT signs of pancreatic trauma. Eight/one hundred and thirty-six (6%) patients underwent surgical treatment and the pancreatic injures were confirmed in all cases. Only in 6/8 patients treated with surgical approach, pancreatic duct damage was suggested in the radiological reports and surgically confirmed in all cases. In 128/136 (94%) patients who underwent non-operative treatment CT images showed pancreatic edema in 97 patients, hematoma in 31 patients, fluid between splenic vein and pancreas in 113 patients. Non-specific CT signs of pancreatic injuries were represented by peri-pancreatic fat stranding and mesentery fluid in 89% of cases, thickening of the left anterior renal fascia in 65%, pancreatic ductal dilatation in 18%, acute pseudocyst/peri-pancreatic fluid collection in 57%, fluid in the pararenal spaces in 45%, fluid in transverse mesocolon and lesser sac in 29%, hemorrhage into peri-pancreatic fat, mesocolon and mesentery in 66%, extraperitoneal fluid in 66%, intra-peritoneal fluid in 41% cases. CONCLUSION: CT represents an accurate tool for diagnosing pancreatic trauma, provides useful information to plan therapeutic approach with a detection rate of 75% for recognizing ductal lesions.

Context: An empty sella is a relatively common condition, often being an incidental finding at MRI or CT scan. It can develop because of the intrasellar herniation of Cerebro-spinal Fluid (CSF) and arachnoid membrane through an absent or rudimentary diaphragm sellae in concomitance of a sudden and even transient increment of intracranial pressure, leading to a picture in which the pituitary is flattened along the floor of the sella. Case Description: A young female with headache, nausea, dizziness, diplopia and visual impairment showed an empty sella on MRI and increased CSF pressure at the lumbar puncture. After an initial improvement, there was a progressive worsening of the headache, especially in orthostatic position, with transient relief after bed rest and hydration. At MRI the empty sella was no longer evident, cerebellar tonsils were displaced in the occipital foramen and there was an impregnation of the meninges after contrast medium, a picture of CSF hypotension, probably due to the previously performed lumbar puncture causing a fistula with leak of CSF and consequent disappearance of the empty sella. The patient gradually improved after being submitted to epidural blood patch. Conclusions: The case here reported demonstrates that an empty sella can be a reversible condition in rare cases. Its disappearance can be due to the reduction in intracranial pressure caused by the lumbar puncture itself. The changes in the characteristics of the headache, in particular its worsening in the orthostatic position, should lead to the suspicion of CSF leak through a fistula and consequent intracranial hypotension, a dangerous and sometimes life-threatening condition.

Introduction Malignant melanoma is one of the most rapidly increasing cancer in the world. Breast metastases from melanoma are uncommon but could reflect a widespread disease. Presentation of case We report a case of malignant widespread melanoma presenting with bilateral breast nodules in a 39 year-old pre-menopausal Caucasian woman with an history of cutaneous melanoma of the trunk. Breast clinical examination revealed the presence of a hard and mobile lump located on the left breast. Ultrasound detected two bilateral nodules corresponding to oval opacities with well-defined edges and without calcifications or architectural distortion on mammography. Fine needle aspiration cytology performed on both breast nodules confirmed that the breast lesions were metastases from primary cutaneous malignant melanoma. A total-body CT examination detected brain, lung and abdominal lymph nodes metastases. Discussion The breast represents an uncommon site of metastatic disease from extra-mammary tumors. Imaging features of breast metastases from melanoma usually do not allow a differential diagnosis with breast primary tumors. Breast metastases may be asymptomatic or palpable as dense and well-circumscribed nodules. Breast metastases indicate a widespread disease and should lead to avoid aggressive surgical procedures because of the poor prognosis of patients affected by metastatic melanoma. Conclusion The detection of bilateral breast metastases from melanoma is highly suggestive of metastatic multi-organ disease and could be useful to address the therapeutic approach.

INTRODUCTIONHepatic angio-sarcoma represents an uncommon malignant tumor of the liver with a poor prognosis and a high rate of bleeding complications.PRESENTATION OF CASEWe report a case of hepatic angio-sarcoma with a multi-nodular pattern complicated by intra-hepatic bleeding. The diagnosis was performed by computed tomography (CT). Angiographic procedure was unsuccessfully attempted as a treatment option. Autoptic examination confirmed the vascular nature of the malignant tumor.DISCUSSIONHepatic angio-sarcoma represents the most common malignant mesenchymal tumor of the liver. The diagnosis is provided by the histological examination and by specific endothelial markers. However, CT examination allows to recognize the disease and to detect intra-abdominal bleeding occurring in one-fourth of cases. Surgical resection represents the only definitive treatment of hepatic angio-sarcoma. In case of haemoperitoneum, trans-catheter arterial embolization represents the primary procedure used to stop the acute arterial bleeding.CONCLUSIONCT represents the reference technique for the diagnosis of hepatic angio-sarcoma and allows to recognize the intra-abdominal bleeding which represents its most common complication. This condition always requires an immediate therapeutic approach.

Aims and Background Computed tomography (CT) does not represent the primary method for the evaluation of breast lesions; however, it can detect breast abnormalities, even when performed for other reasons related to thoracic structures. The aim of this study is to evaluate the potential benefits of 320-row multidetector CT (MDCT) in evaluating and differentiating incidentally detected breast lesions by using vessel probe and 3D analysis software with net enhancement value. Methods and Study design Sixty-two breast lesions in 46 patients who underwent 320-row chest CT examination were retrospectively evaluated. CT scans were assessed searching for the presence, location, number, morphological features, and density of breast nodules. Net enhancement was calculated by subtracting precontrast density from the density obtained by postcontrast values. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy of CT were calculated for morphological features and net enhancement. Results Thirty of 62 lesions were found to be malignant at histological examination and 32 were found to be benign. When morphological features were considered, the sensitivity, specificity, accuracy, PPV, and NPV of CT were 87%, 100%, 88%, 100%, and 50%, respectively. Based on net enhancement, CT reached a sensitivity, specificity, accuracy, PPV, and NPV of 100%, 94%, 97%, 94%, and 100%, respectively. Conclusions MDCT allows to recognize and characterize breast lesions based on morphological features. Net enhancement can be proposed as an additional accurate feature of CT.

Objectives Diffusion-weighted imaging with background body signal suppression (DWIBS) provides both qualitative and quantitative imaging of breast lesions and are usually performed before contrast material injection (CMI). This study aims to assess whether the administration of gadolinium significantly affects DWIBS imaging. Methods 200 patients were prospectively evaluated by MRI with STIR, TSE-T2, pre-CMI DWIBS, contrast enhanced THRIVE-T1 and post-CMI DWIBS sequences. Pre and post-CMI DWIBS were analyzed searching for the presence of breast lesions and calculating the ADC value. ADC values of ≤ 1.44 × 10- 3 mm2/s were considered suspicious for malignancy. This analysis was then compared with the histological findings. Sensitivity, specificity, diagnostic accuracy (DA), positive predictive value (PPV) and negative (NPV) were calculated for both sequences and represented by ROC analysis. Pre and post-CMI ADC values were compared by using the paired t test. Results In 150/200 (59%) patients, pre and post-CMI DWIBS indicated the presence of breast lesions, 53 (35%) with ADC values of > 1.44 × 10- 3 mm2/s and 97 (65%) with ADC ≤ 1.44 × 10- 3 mm2/s. Pre-CMI and post-DWIBS sequences obtained the same sensitivity, specificity, DA, PPV and NPV values of 97%, 83%, 89%, 79% and 98%. The mean ADC value of benign lesions was 1.831 ± 0.18 × 10- 3 mm2/s before and 1.828 ± 0.18 × 10- 3 mm2/s after CMI. The mean ADC value of the malignant lesions was 1.146 ± 0.16 × 10- 3 mm2/s before and 1.144 ± 0.16 × 10- 3 mm2/s after CMI. No significant difference was found between pre and post CMI ADC values (p > 0.05). Conclusion DWIBS imaging is not influenced by CMI. Breast MR protocol could be modified by placing DWIBS after dynamic contrast enhanced sequences in order to maximize patient cooperation.

Acute intestinal ischemia is an abdominal emergency occurring in nearly 1% of patients presenting with acute abdomen. The causes can be occlusive or non occlusive. Early diagnosis is important to improve survival rates. In most cases of late or missed diagnosis, the mortality rate from intestinal infarction is very high, with a reported value ranging from 60% to 90%. Multi-detector computed tomography (MDCT) is a fundamental imaging technique that must be promptly performed in all patients with suspected bowel ischemia. Thanks to the new dedicated reconstruction program, its diagnostic potential is much improved compared to the past and currently it is superior to that of any other noninvasive technique. The increased spatial and temporal resolution, high-quality multi-planar reconstructions, maximum intensity projections, vessel probe, surface-shaded volume rending and tissue transition projections make MDCT the gold standard for the diagnosis of intestinal ischemia, with reported sensitivity, specificity, positive and negative predictive values of 64%-93%, 92%-100%, 90%-100% and 94%-98%, respectively. MDCT contributes to appropriate treatment planning and provides important prognostic information thanks to its ability to define the nature and extent of the disease. The purpose of this review is to examine the diagnostic and prognostic role of MDCT in bowel ischemia with special regard to the state of art new reconstruction software.

Objectives Diffusion imaging represents a new imaging tool for the diagnosis of breast cancer. This study aims to investigate the role of diffusion-weighted MRI with background body signal suppression (DWIBS) for evaluating breast lesions. Methods 90 patients were prospectively evaluated by MRI with STIR, TSE-T2, contrast enhanced THRIVE-T1 and DWIBS sequences. DWIBS were analyzed searching for the presence of breast lesions and calculating the ADC value. ADC values of ≤ 1.44 × 10 - 3 mm 2 /s were considered suspicious for malignancy. This analysis was then compared with the histological findings. Sensitivity, specificity, diagnostic accuracy (DA), positive predictive value (PPV) and negative (NPV) were calculated. Results In 53/90 (59%) patients, DWIBS indicated the presence of breast lesions, 16 (30%) with ADC values of > 1.44 and 37 (70%) with ADC ≤ 1.44. The comparison with histology showed 25 malignant and 28 benign lesions. DWIBS sequences obtained sensitivity, specificity, DA, PPV and NPV values of 100, 82, 87, 68 and 100%, respectively. Conclusion DWIBS can be proposed in the MRI breast protocol representing an accurate diagnostic complement.

The purpose of this study was to evaluate the computed tomography (CT) signs of free and covered small-bowel perforations and the potential of CT in recognising the aetiology. Thirty-five patients with surgically proven small-bowel perforation were retrospectively evaluated. Fundamental signs (extraluminal air, solution of continuity) and secondary signs (thickening of the mesentery, free or perilesional fluid, wall thickening) were considered. CT alterations were found in 31/35 (88.6 %) patients: extraluminal air (30/35, 85.7 %), solution of continuity (11/35, 31.4 %), intra-abdominal fluid (27/35, 77.1 %), thickening of the mesentery (20/35, 57.1 %), and wall thickening (14/35, 40 %). In 25/35 cases (71.4 %) pneumoperitoneum was detected, associated with secondary signs (23/25, 82 %), confirmed as free perforations at surgery. In 5/35 patients (14.2 %), peri-intestinal air bubbles and secondary signs were evident, while in 1/35 cases (2.8 %) only secondary signs were seen, namely covered perforations. In 4/35 patients (11.4 %) with a covered perforation, the CT scan was negative. The nature of the perforations was completely recognisable in 26/31 cases (83.9 %), partially identifiable in 4/31 (12.9 %), not evident in 1/31 (3.2 %). CT investigation is essential in the recognition of a small-bowel perforation and in the definition of its nature.

Purpose. To evaluate the accuracy of the washout in the differential diagnosis between adenomas and nonadenomas and to compare the obtained results in delayed CT scans at 5, 10 and 15 minutes.Methods. Fifty patients with adrenal masses were prospectively evaluated. CT scans were performed by using a 320-row MDCT device, before and after injection of contrast material. In 25 cases, delayed scans were performed at 5′ and 10′ (group 1), while in the remaining 25, at 5′ and 15′ (group 2). Absolute and relative wash-out percentage values (APW and RPW) were calculated.Results. Differential diagnosis between adenomas and nonadenomas was obtained in 48/50 (96%) cases, with sensitivity, specificity, and accuracy values of 96%, 95%, and 96%, respectively. In group 1, APW and RPW values were, respectively, 69.8% and 67.2% at 5′ and 75.9% and 73.5% at 10′ for adenomas and 25.1% and 15.8% at 5′ and 33.5% and 20.5% at 10′ for nonadenomas. In group 2, APW and RPW values were 63% and 54.6% at 5′ and 73.8% and 65.5% at 15′ for adenomas and 22% and 12.5% at 5′ and 35.5% and 19.9% at 15′ for nonadenomas.Conclusions. The evaluation of the wash-out values in CT scans performed at 5′, 10′, and 15′ provides comparable diagnostic results. CT scans performed at 5′ are, therefore, to be preferred, since they reduce the examination time and patient discomfort.