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Aim of this study is to compare early post-operative outcomes and patient’s satisfaction after skin-sparing and/or nipple-sparing mastectomy (SSM/SNSM) followed either by breast reconstruction with one-stage prepectoral implantation or two-stage technique for breast cancer (BC) or BRCA1/2 mutation.From January 2018 to December 2021, 96 patients (mean age of 51.12 ± 10.9) underwent SSM/SNSM and were divided into two groups: in group A (65 patients, 67.7%), mastectomy was followed by one-stage reconstruction; in group B (31 patients, 32.3%) by two-stage. Operative time was significantly longer in A vs. B (307.6 ± 95.7 vs. 254.4 ± 90.91; P P P = 0.001). All SSM/SNSM for BRCA1/2 mutation were followed by immediate prepectoral implantation. No significant differences were found between groups in terms of post-operative complications. At pathology, DCIS and invasive ST forms, such as multicentric/multifocal forms, were detected more frequently in B, while NST type in A (all P P = 0.001). Encouraging oncologic outcomes after SSM/SNSM for BC enabled the improvement of breast reconstructive techniques. One-stage reconstruction is characterized by better aesthetic outcomes and by greater patient’s satisfaction. When SSM/SNSM is technically difficult to perform, as in multicentric/multifocal forms or previous breast surgery, mastectomy followed by two-stage reconstruction should be considered to achieve a radical surgery.

Objectives To develop an intuitive and generally applicable system for the reporting, assessment, and documentation of ADC to complement standard BI-RADS criteria. Methods This was a multicentric, retrospective analysis of 11 independently conducted institutional review board–approved studies from seven institutions performed between 2007 and 2019. Breast Apparent Diffusion coefficient (ADC-B) categories comprised ADC-B0 (ADC non-diagnostic), ADC-B1 (no enhancing lesion), and ADC-B2-5. The latter was defined by plotting ADC versus cumulative malignancy rates. Statistics comprised ANOVA with post hoc testing and ROC analysis. p values ≤ 0.05 were considered statistically significant. Results A total of 1625 patients (age: 55.9 years (± 13.8)) with 1736 pathologically verified breast lesions were included. The mean ADC (× 10−3 mm2/s) differed significantly between benign (1.45, SD .40) and malignant lesions (.95, SD .39), and between invasive (.92, SD .22) and in situ carcinomas (1.18, SD .30) (p 24.5%). At the latter threshold, a positive predictive value of 95.8% (95% CI 0.94–0.97) for invasive versus non-invasive breast carcinomas was reached. Conclusions The breast apparent diffusion coefficient system (ADC-B) provides a simple and widely applicable categorization scheme for assessment, documentation, and reporting of apparent diffusion coefficient values in contrast-enhancing breast lesions on MRI. Clinical relevance statement The ADC-B system, based on diverse MRI examinations, is clinically relevant for stratifying breast cancer risk via apparent diffusion coefficient measurements, and complements BI-RADS for improved clinical decision-making and patient outcomes. Key Points • The breast apparent diffusion coefficient category system (ADC-B) is a simple tool for the assessment, documentation, and reporting of ADC values in contrast-enhancing breast lesions on MRI. • The categories comprise ADC-B0 for non-diagnostic examinations, ADC-B1 for examinations without an enhancing lesion, and ADC-B2-5 for enhancing lesions with an increasing malignancy rate. • The breast apparent diffusion coefficient category system may be used to complement BI-RADS in clinical decision-making.

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.

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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.

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 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.

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.

The onset characteristics of the anaplastic large cell lymphoma (BI-ALCL) are non-specific and the diagnosis is often difficult and based on clinical suspicion and cytological sampling. The presence of non-pathognomonic radiological signs may delay the diagnosis of BI-ALCL, influencing patient prognosis. This could have an important social impact, considering that the incidence of BI-ALCL correlates with the number of prosthetic implants, which is in constant increase worldwide. The aim of this study was to verify if fibrin can represent a potential early radiological sign of the disease.In this study, we present two cases of our series and review the previous studies already described in literature, searching for any early radiological sign of the disease and reporting a diagnostic work-up process for an early diagnosis.Signs clearly recognizable only of magnetic resonance were the following: thickening and hyperemia of the fibrous capsule with seroma and amorphous material (fibrin) present in 8 out of 10 cases (80%) detected on magnetic resonance images (certain or doubtful).The presence of fibrin in the periprosthetic effusion, well detectable by magnetic resonance imaging, could represent an early pathognomonic sign of the disease.

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.

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.

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.

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.

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.

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.