Purpose: To test the potential impact of pharmacokinetic parameters, derived from DCE-MRI analysis, on the diagnostic performance of PI-RADSv.2 classification in prostate lesions characterization. Method: Among patients who underwent multiparametric prostate MRI (mpMRI) (January 2016-March 2018) followed by histological evaluation (targeted biopsies/prostatectomy), 103 men were retrospectively selected. For each patient the index lesion was identified and pharmacokinetic parameters (Ktrans, Kep, Ve, Vp) were assessed. MRI diagnostic performance in the detection of significant tumors [Gleason Score (GS) >= 7] was assessed, considering PI-RADS >= 3 as positive. Results: GS >= 7 (n = 59) showed higher Ktrans (p < 0.01) and Kep (p = 0.01) compared to GS < 7. At ROC curve analysis, a Ktrans cut-off of 191 x 10(-3) /min was identified to predict the presence of GS >= 7 (AUC:0.75; sensitivity:95%; specificity:61%). Sensitivity and PPV of mpMRI using PI-RADSv.2 were 98% and 61%. Reclassifying PI-RADS >= 3 lesions according to Ktrans cut-off, 22 false positives were shifted to true negatives with 3 false negative findings; PPV raised to 79%. Appling Ktrans cut-off to PI-RADS 3 lesions of peripheral zone (n = 18), 12 true negatives, 4 true positives, 2 false positives were identified. Conclusions: Despite its high sensitivity prostate mpMRI generates many false positive cases: Ktrans in addition to PIRADS v.2 seems to improve MRI-PPV and may help in avoiding redundant biopsies.

Diffuse remodeling of myocardial extra-cellular matrix is largely responsible for left ventricle (LV) dysfunction and arrhythmias. Our hypothesis is that the texture analysis of late iodine enhancement (LIE) cardiac computed tomography (cCT) images may improve characterization of the diffuse extra-cellular matrix changes. Our aim was to extract volumetric extracellular volume (ECV) and LIE texture features of non-scarred (remote) myocardium from cCT of patients with recurrent ventricular tachycardia (rVT), and to compare these radiomic features with LV-function, LV-remodeling, and underlying cardiac disease.Forty-eight patients suffering from rVT were prospectively enrolled: 5/48 with idiopathic VT (IVT), 23/48 with post-ischemic dilated cardiomyopathy (ICM), 9/48 with idiopathic dilated cardiomyopathy (IDCM), and 11/48 with scars from a previous healed myocarditis (MYO). All patients underwent echocardiography to assess LV systolic and diastolic function and cCT with pre-contrast, angiographic, and LIE scan to obtain end-diastolic volume (EDV), ECV, and first-order texture parameters of Hounsfield Unit (HU) of remote myocardium in LIE [energy, entropy, HU-mean, HU-median, standard deviation (SD), and mean absolute deviation (MAD)].Energy, HU mean, and HU median by cCT texture analysis correlated with ECV (rho = 0.5650, rho = 0.5741, rho = 0.5068; p < 0.0005). cCT-derived ECV, HU-mean, HU-median, SD, and MAD correlated directly to EDV by cCT and inversely to ejection fraction by echocardiography (p < 0.05). SD and MAD correlated with diastolic function by echocardiography (rho = 0.3837, p = 0.0071; rho = 0.3330, p = 0.0208). MYO and IVT patients were characterized by significantly lower values of SD and MAD when compared with ICM and IDCM patients, independently of LV-volume systolic and diastolic function.Texture analysis of LIE may expand cCT capability of myocardial characterization. Myocardial heterogeneity (SD and MAD) was associated with LV dilatation, systolic and diastolic function, and is able to potentially identify the different patterns of structural remodeling characterizing patients with rVT of different etiology.

Live-cell microscopy revealed the transient nature of transcription factors (TFs) binding to chromatin. However, it is still not clear whether the duration of these binding interactions can be tuned in response to an activating stimulus, and whether such modulation can control the transactivation of target genes. To cover this issue we focused on the tumor-suppressor p53 by combining live-cell single molecule tracking and single cell in-situ measurements of transcription. We show that the fraction of chromatin bound p53 and its residence time are increased following genotoxic stress. Moreover, we found that the modulation of p53 residence time on chromatin requires post translational modifications (PTMs) and correlates with the induction of transcription of target genes. These results allowed us to depict a model in which the modification state of the TF, that accompanies its increase, determines the TF transcriptional activity by tuning its residence time on target sites. Our findings could have an important relevance for those cancers that express an inactive wild type form of p53, like neuroblastoma (NS), in which has been recently reported a defect in PTMs of p53. Thus, we are currently performing SMT measurements in NS cell line to verify whether p53 binding kinetics are affected and we aim to restore the proper PTMs in order to rescue p53 binding kinetics and its transactivation potential in these cancers.

Live-cell microscopy has highlighted that transcription factors bind transiently to chromatin but it is not clear if the duration of these binding interactions can be modulated in response to an activation stimulus, and if such modulation can be controlled by post-translational modifications of the transcription factor. We address this question for the tumor suppressor p53 by combining live-cell single-molecule microscopy and single cell in situ measurements of transcription and we show that p53-binding kinetics are modulated following genotoxic stress. The modulation of p53 residence times on chromatin requires C-terminal acetylation-a classical mark for transcriptionally active p53-and correlates with the induction of transcription of target genes such as CDKN1a. We propose a model in which the modification state of the transcription factor determines the coupling between transcription factor abundance and transcriptional activity by tuning the transcription factor residence time on target sites.Both transcription binding kinetics and post-translational modifications of transcription factors are thought to play a role in the modulation of transcription. Here the authors use single-molecule tracking to directly demonstrate that p53 acetylation modulates promoter residence time and transcriptional activity.

Purpose: An accurate prediction of tumour response to therapy is fundamental in oncology, so as to prompt personalised treatment options if needed.The aim of this study was to investigate the ability of preoperative texture analysis from multi-detector computed tomography (MDCT) in the prediction of the response rate to neo-adjuvant therapy in patients with gastric cancer.Material and methods: Thirty-four patients with biopsy-proven gastric cancer were examined by MDCT before neo-adjuvant therapy, and treated with radical surgery after treatment completion. Tumour regression grade (TRG) at final histology was also assessed. Image features from texture analysis were quantified, with and without filters for fine to coarse textures. Patients with TRG 1-3 were considered responders while TRG 4-5 as non-responders. The response rate to neo-adjuvant therapy was assessed both at univariate and multivariate analysis.Results: Fourteen parameters were significantly different between the two subgroups at univariate analysis; in particular, entropy and compactness (higher in responders) and uniformity (lower in responders). According to our model, the following parameters could identify non-responders at multivariate analysis: entropy (<= 6.86 with a logarithm of Odds Ratio - Log OR -: 4.11; p = 0.003); range (> 158.72; Log OR: 3.67; p = 0.010) and root mean square (<= 3.71; Log OR: 4.57; p = 0.005). Entropy and three-dimensional volume were not significantly correlated (r = 0.06; p = 0.735).Conclusion: Pre-treatment texture analysis can potentially provide important information regarding the response rate to neo-adjuvant therapy for gastric cancer, improving risk stratification. (C) 2017 Elsevier B.V. All rights reserved.

Human identification is one of the primary objectives in a forensic context. In this respect, studies concerning the skeletal anatomical variations have revealed a great potential. These variants are used as secondary identification method within the scope of the assessment of ancestry and of the factors of personal identity in the reconstructive and comparative phases. However, not only are there few studies about the postcranial skeletal variants, but also there are a couple of current publications and most of the samples are not contemporary. The purpose of the present research is to obtain the frequency of asymptomatic osseous variants (AOV) of the postcranial skeleton in a current identified Portuguese sample. The present study addresses only the partial results for the upper limb, thorax, and lower limb. Altogether, 58 anatomical variants were analyzed. The sample includes 282 contemporary adult skeletons (148 females and 134 males) belonging to the 21st Century Identified Skeletal Collection housed in the Laboratory of Forensic Anthropology, University of Coimbra. The classification pattern of the variants is binary (0 for absent and 1 for present) and bilateral. The results show frequencies for the rarest ones with frequencies lower than 1% (duplication of acromial extremity of the clavicle, misplaced manubriosternal joint and dorsal defect of the patella) to the most frequent ones with frequencies greater than 50% (ulnar medial trochlear notch form, suprascapular notch and bipartite anterior facet of the calcaneus). The detection of an AOV in an unidentified skeleton, besides being an identity factor, could allow allocating that individual to a population where the same characteristic is very frequent. Therefore, the results provide contributions to human identification and can be used whenever a case of forensic anthropology is made.

To investigate the association between preoperative texture analysis from multidetector computed tomography (MDCT) and overall survival in patients with gastric cancer.

OBJECTIVES This study sought to compare myocardial scars depicted by computed tomography (CT) with electrical features from electro-anatomic mapping (EAM), assessing the potential role of CT integration in ventricular tachycardia (VT) and radiofrequency catheter ablation (RFCA) procedures.BACKGROUND Imaging-based characterization of VT myocardial substrate is required to plan EAM and, potentially, to guide RFCA.METHODS Forty-two consecutive patients, 35 of whom had implantable cardioverter-defibrillator, all referred for VT RFCA, underwent pre-procedural CT including an angiographic and a 10-min delayed-enhancement scan. Segmental comparison between scars segmented from CT and low voltages (bipolar voltages <1.5 mV; unipolar voltages <8 mV), late potentials, and RF ablation points on EAM, was carried out. In a subset of 16 consecutive patients, a further point-by-point analysis was performed: a CT-derived 3-dimensional structure including heart anatomy and myocardial scars was integrated with EAM for quantitative comparison.RESULTS CT scans identified scars in 39 patients and defined left ventricular wall involvement and mural distribution. Overall segmental concordance between CT and EAM was good (kappa = 0.536) despite the presence of implantable cardioverter-defibrillator, scar etiologies, and mural distribution. CT identified segments characterized by low voltages with good sensitivity (76%), good specificity (86%), and very high negative predictive value (95%). Late potentials and RF ablation points fell on scarred segments identified from CT in 79% and 81% of cases, respectively. Point-by-point quantitative comparison revealed good correlation between the average area of scar detected at CT and at bipolar mapping (CT = 4,901 mm(2), bipolar voltages-EAM = 4,070 mm(2); R = 0.78; p < 0.0001). In this study, 70% and 84% of low-amplitude bipolar points were mapped at a maximum distance of 5 mm and 10 mm from CT-segmented scar, respectively.CONCLUSIONS CT with delayed-enhancement provides a 3-dimensional characterization of VT scar substrate together with a detailed anatomic model of the heart. This information may offer assistance to plan EAM and RFCA procedures and is potentially suitable for EAM-imaging integration. (C) 2016 by the American College of Cardiology Foundation.

Extraction of the cardiac surfaces of interest from multi-detector computed tomographic (MDCT) data is a pre-requisite step for cardiac analysis, as well as for image guidance procedures. Most of the existing methods need manual corrections, which is time-consuming. We present a fully automatic segmentation technique for the extraction of the right ventricle, left ventricular endocardium and epicardium from MDCT images. The method consists in a 3D level set surface evolution approach coupled to a new stopping function based on a multiscale directional second derivative Gaussian filter, which is able to stop propagation precisely on the real boundary of the structures of interest. We validated the segmentation method on 18 MDCT volumes from healthy and pathologic subjects using manual segmentation performed by a team of expert radiologists as gold standard. Segmentation errors were assessed for each structure resulting in a surface-to-surface mean error below 0.5 mm and a percentage of surface distance with errors less than 1 mm above 80%. Moreover, in comparison to other segmentation approaches, already proposed in previous work, our method presented an improved accuracy (with surface distance errors less than 1 mm increased of 8-20% for all structures). The obtained results suggest that our approach is accurate and effective for the segmentation of ventricular cavities and myocardium from MDCT images.

An accurate detection of myocardial scar using Cardiac CT may have a strong clinical impact; however, the main drawback is the insufficient contrast to noise ratio of delayed iodine enhanced (DIE) CT images, which makes its accurate segmentation (manual as well as automatic) difficult. In this work, we investigate texture parameters applied on the different scans in order to obtain the scans and features that best differentiates normal from scarred myocardium. The experiments on 7 cases of myocarditis show the accuracy of the parameter energy in all scans, as well as the good performance of the angiographic scan (having higher spatial resolution) with different parameters for the segmentation propose. Moreover, the best performance was obtained on the baseline scan for the energy feature, with an accuracy of 94%.

Autosomal dominant polycystic kidney disease (ADPKD) is an important cause of ESRD for which there exists no approved therapy in the United States. Defective glucose metabolism has been identified as a feature of ADPKD, and inhibition of glycolysis using glucose analogs ameliorates aggressive PKD in preclinical models. Here, we investigated the effects of chronic treatment with low doses of the glucose analog 2-deoxy-d-glucose (2DG) on ADPKD progression in orthologous and slowly progressive murine models created by inducible inactivation of the Pkd1 gene postnatally. As previously reported, early inactivation (postnatal days 11 and 12) of Pkd1 resulted in PKD developing within weeks, whereas late inactivation (postnatal days 25-28) resulted in PKD developing in months. Irrespective of the timing of Pkd1 gene inactivation, cystic kidneys showed enhanced uptake of (13)C-glucose and conversion to (13)C-lactate. Administration of 2DG restored normal renal levels of the phosphorylated forms of AMP-activated protein kinase and its target acetyl-CoA carboxylase. Furthermore, 2DG greatly retarded disease progression in both model systems, reducing the increase in total kidney volume and cystic index and markedly reducing CD45-positive cell infiltration. Notably, chronic administration of low doses (100 mg/kg 5 days per week) of 2DG did not result in any obvious sign of toxicity as assessed by analysis of brain and heart histology as well as behavioral tests. Our data provide proof of principle support for the use of 2DG as a therapeutic strategy in ADPKD.

Durante la mappatura elettroanatomica e la procedura di ablazione, l'esatta localizzazione della cicatrice miocardiaca e importante per decidere se la procedura sara epicardiaca o endocardiaca, cosi come per ridurre il tempo d'intervento. Oggi, la risonanza magnetica con mezzo di contrasto e considerato il gold standard per valutare il tessuto miocardiaco. Tuttavia, la TAC potrebbe essere un interessante alternativa. Le principali ragioni sono la riduzione degli artefatti causata dal defibrillatore, la maggiore risoluzione spaziale e l'affidabilita nella visualizzazione del grasso epicardiaco quando confrontata con la risonanza. Nell'identificazione dei circuiti di rientro durante un intervento epicardiaco, la conoscenza della localizzazione del grasso epicardiaco e utile, perche il grasso presenta caratteristiche di voltaggio simili al tessuto cicatriziale ed e spesso confuso con quest'ultimo. Tuttavia, il grasso e spesso trascurato nelle procedure di ablazione perche richiede una onerosa segmentazione manuale. Lo scopo di questo lavoro e stato costruire un modello 3D multi parametrico del cuore, segmentando automaticamente le cavita ventricolari, il miocardio sinistro, la cicatrice, il grasso epicardiaco e le coronarie da immagini TAC. Per la segmentazione anatomica e stato sviluppato un’algoritmo level set basato su un filtro multiscala e direzionale. La cicatrice miocardiaca e stata segmentata analizzando lo scan tardivo e/o l’assottigliamento della parete miocardiaca. Questo approccio e stato applicato su pazienti con tachicardia ventricolare ricorrente. L’accuratezza del nostro modello e stata verificata confrontandolo con le segmentazioni manuali di esperti radiologi e con i risultati della mappa elettroanatomica creata dall’aritmologo durante l’intervento di mappatura. I risultati suggeriscono che il nostro metodo potrebbe essere integrato nel software di ablazione a radiofrequenza come uno strumento efficace per assistere l’aritmologo durante l’intervento.

Poster: ECR 2015 / B-0180 / Point-by-point correlation between electroanatomic mapping (EAM) and 3D-model from multidectector-computed tomography (3D-CT-model) in patients affected by ventricular tachycardia (VT) by: C. Colantoni, A. Esposito, A. Palmisano, S. Antunes, F. De Cobelli, G. Maccabelli, P. Della Bella, G. Rizzo, A. Del Maschio; Milan/IT

The purpose of this work was to compare an image-based parametric myocardium mesh automatically segmented from multidetector computed tomographic (MDCT) volumes with the findings of electro-anatomic maps (EAM) constructed previously to radiofrequency ablation (RFa) procedures. The myocardium mesh presents distance information about myocardial thickness, as well as the localization of scar detected using a delayed enhanced DE-MDCT scan. Additionally, possible zones of epicardial fat with thickness greater than 3mm were also identified on patients that underwent an epicardial intervention. The comparison was performed on 5 patients with recurrent ventricular tachycardia (VT) undergoing angiographic and DE-MDCT scan before EAM and RFa, of which 3 patients underwent endocardial and 2 patients an epicardial procedure. We compared the findings of the myocardium mesh against EAM and our results suggest that the mesh could be an important tool for the prediction of myocardial scar localization.

We present a novel approach for the automatic segmentation of the right ventricle in CT images. We use a level set with a new multi-scale edge stopping function based on spatial oriented filters. This stopping function reduces false edge detection and over-segmentation. The segmentation method was evaluated over 18 CT image studies from healthy and pathologic subjects; results are compared against manual segmentation made by a team of expert radiologists. The mean surface distance error is below 0.64 mm, which proves the effectiveness of the method.

The purpose of this work was to construct a 3D multi-parametric model of the heart by automatically segmenting cardiac cavities, left myocardium, scar and epicardial fat from multidetector computed tomographic (MDCT) volumes, using a level set algorithm based on a new multi-scale stopping function. This method was applied to 4 patients with recurrent ventricular tachycardia (VT) undergoing contrast enhanced (CE)-MDCT imaging, composed by an angiographic (ANGIO) and a late enhanced (LE) scan, before electro-anatomic mapping (EAM) and radiofrequency ablation (RFa). The segmented structures were integrated into the clinical surgery software system (CARTO). The adequacy of our model was verified by an expert radiologist and an arrhythmologist using a qualitative score.

Segmentation of echocardiographic images presents a great challenge because these images contain strong speckle noise and artifacts. Besides, most ultrasound segmentation methods are semi-automatic, requiring initial contour to be manually identified in the images. In this work, we propose an algorithm based on the phase symmetry approach and level set evolution, in order to extract simultaneously all heart cavities in a fully automatic way. The level set evolution uses a new logarithmic based stopping function, which demonstrates to perform well in the boundary extraction. We compared our method with other level set approaches, the watershed technique, and the manual segmentation made by two physicians. The experimental work was based on echocardiography images of children. Similarity metrics, namely Pratt Function, Pixel Mean Error, and Similarity Angle have been used for the performance evaluation of the different methods. The results indicate that our method has a performance at least 4% superior to the other methods able to segment the four chambers. Even for the two worst boundary extraction cases (right ventricle and left atrium) the performance of the proposed method still is better than the other techniques.

Ultrasonography is one of the safest methods in medical imaging, however the segmentation of such images still is a difficult task. A robust segmentation of the heart cavities and a 3D view are needed to better understand the congenital malformations and defects in children hearts. In this work we propose an automatic segmentation method based on geometric models to extract the boundaries of the four heart cavities, by an algorithm that uses the phase symmetry. The performance of the proposed method is quantitatively compared with three alternative level set functions, the watershed segmentation and the contours drawn by a pediatrician.