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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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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 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.

To evaluate spatial displacement of breast lesions from prone MR to supine ultrasound positions, and to determine whether the degree of displacement may be associated with breast density and lesion histotype.380 patients underwent breast MR and second-look ultrasound. The MR and ultrasound lesion location within the breast gland, distances from anatomical landmarks (nipple, skin and pectoral muscle), spatial displacement (distance differences from the landmarks within the same breast region) and region displacement (breast region change) were prospectively evaluated. Differences between MR and ultrasound measurements, association between the degree of spatial displacement and both breast density and lesion histotypes were calculated.In 290/380 (76%) patients, 300 MR lesions were detected. 285/300 (95%) lesions were recognized on ultrasound. By comparing MR and ultrasound, spatial displacement occurred in 183/285 (64.3%) cases while region displacement in 102/285 (35.7%) cases with a circumferential movement along an arc centred on the nipple, having supine ultrasound as the reference standard. A significant association between the degree of lesion displacement and breast density was found (p 0.00001) with a significant higher displacement in case of fatty breasts. No significant association between the degree of displacement and lesion histotype was found (p = 0.1).Lesion spatial displacement from MRI to ultrasound may occur especially in adipose breasts. Lesion-nipple distance and circumferential displacement from the nipple need to be considered for ultrasound lesion detection.Second-look ultrasound breast lesion detection could be improved by calculating the lesion-nipple distance and considering that spatial displacement from MRI occurs with a circumferential movement along an arc centred on the nipple.

This study aims to assess the diagnostic accuracy of virtual gastroscopy obtained by 320-row computed tomography (CT) examination in differentiating benign from malignant gastric ulcers (GUs). 49 patients (30 M, 19 F, mean age 58.6) with endoscopic and histological diagnosis of GU underwent CT examination. A hypotonizing drug was administered and gastric walls were distended by air in order to perform virtual endoscopy. Based on morphological features, GUs were subdivided into benign or malignant forms by two blinded radiologists. Interobserver agreement was evaluated using Cohen’s kappa (k) test. CT results were then compared with endoscopic and histological findings, having the latter as the reference standard. Thirty-five out of 49 patients (71%) were affected by malignant ulcers, while in the remaining 14 cases diagnosis of benign GU was made. Virtual gastroscopy showed diagnostic accuracy, sensitivity, and specificity values of 94%, 91%, and 100%, respectively, in differentiating benign from malignant ulcers. Almost perfect agreement between the two readers was found (k = 0.86). CT virtual gastroscopy improves the identification of GUs and allows differentiating benign from malignant forms.

The occurrence of false-positives (FPs) is still an important concern and source of unreliability in computer-aided diagnosis systems developed for 3D virtual colonoscopy. This work presents three different supervised approaches, based on supervised artificial neural networks (ANNs) architectures tested on 16 rows helical multi-slice computer tomography. The performance of the best ANN architecture developed, by using the volumes belonging to only 4 of 7 available nodules diagnosed by expert radiologists as polyps and non-polyps were evaluated in terms of FPs and false-negatives. It revealed good performance in terms of generalization and FPs reduction, correctly detecting all 7 polyps.

Diagnostic imaging provides useful anatomical and morphological information of cervico-mediastinal goiters. The aim of this study was to assess the usefulness of multidetector computed tomography (MDCT) with multiplanar reformatting and volume rendering reconstructions for the preoperative evaluation of retrosternal goiters in patients for whom magnetic resonance imaging is contraindicated.From March 2006 to January 2009, 34 patients (20 women and 14 men; mean age, 48 years; range, 42-74 years) with suspected cervico-mediastinal goiter were assessed by MDCT after intravenous injection of contrast material. The following parameters were evaluated: morphology, size, and enhancement of thyroid lobes; presence, location, and mediastinal extension of thyroid tissue; and relations with mediastinal vessels and organs. All patients underwent thyroidectomy. A reference group of 34 patients evaluated by single-detector computed tomography was created. The two groups of patients were compared searching for operative time (OT, in hours), hospital stay (HS, in days), and morbidity rate observed after thyroid surgery in all cases.In 29/34 patients, thyroid was enlarged with left mediastinal extension in 12 cases, right extension in 10 cases, and posterior extension in 7 cases. In 3/34 patients, a normal cervical thyroid connected to the mediastinal goiter through a thin parenchymal stripe was observed. In 2/34 patients, thyroid lobes were enlarged, without mediastinal extension. By comparing the two groups of patients for OT and HS values, a significant reduction to 3.7 +/- 0.1 hours and 4.3 +/- 0.1 days, respectively, was found in the group of MDCT patients, and also a trend to the reduction for morbidity rate (21%) could be recognized.MDCT represents a noninvasive tool in the evaluation of retrosternal goiters. High-quality multiplanar reformatting and volume rendering reconstructions allow an optimal analysis of the plunged gland and could reduce OT, HS, and probably the morbidity rate.

This paper describes a complete image processing framework for Virtual Colonscopy. The developed algorithms cover the entire process that allows a virtual navigation inside the colon lumen, starting from a dataset of axial CT slices. The implemented modules are: electronic colon cleansing, lumen segmentation, skeletonization, rendering and navigation. In particular for the centerline problem two different techniques are proposed and evaluated.

The purpose of the report was to evaluate the role of fluorine-18 fluoro-2-deoxy-d-glucose positron emission tomography/computed tomography (18F-FDG PET/CT) in staging gastric cancer comparing it with contrast enhancement computed tomography (CECT). This retrospective study included 45 patients who underwent performed whole body CECT and 18F-FDG PET/CT before any treatment. We calculated CECT and 18F-FDG PET/CT sensitivity, specificity, accuracy, positive and negative predictive values (PPV and NPV) for gastric, lymphnode, and distant localizations; furthermore, we compared the 2 techniques by McNemar test. The role of 18F-FDG PET/CT semiquantitative parameters in relation to histotype, grading, and site of gastric lesions were evaluated by ANOVA test. Sensitivity, specificity, accuracy, PPV and NPV of CECT, and 18F-FDG PET/CT for gastric lesion were, respectively, 92.11%, 57.14%, 86.66%, 92.11%, 57.14% and 81.58%, 85.71%, 82.22%, 96.88%, 46.15%. No differences were identified between the 2 techniques about sensitivity and specificity. No statistical differences were observed between PET parameters and histotype, grading, and site of gastric lesion. The results of CECT and 18F-FDG PET/CT about lymphnode involvement were 70.83%, 61.90%, 66.66%, 68%, 65% and 58.33%, 95.24%, 75.55%, 93.33%, 66.67%. The results of CECT and 18F-FDG PET/CT about distant metastases were 80%, 62.86%, 66.66%, 38.10%, 91.67% and 60%, 88.57%, 82.22%, 60%, 88.57%. 18FDG PET/CT specificity was significantly higher both for lymphnode and distant metastases. The 18F-FDG PET/CT is a useful tool for the evaluation of gastric carcinoma to detect primary lesion, lymphnode, and distant metastases using 1 single image whole-body technique. Integration of CECT with 18F-FDG PET/CT permits a more valid staging in these patients.