22,662 research outputs found

    Tumors in von Hippel–Lindau Syndrome: From Head to Toe—Comprehensive State-of-the-Art Review

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    Von Hippel–Lindau syndrome (VHL) is an autosomal-dominant hereditary tumor disease that arises owing to germline mutations in the VHL gene, located on the short arm of chromosome 3. Patients with VHL may develop multiple benign and malignant tumors involving various organ systems, including retinal hemangioblastomas (HBs), central nervous system (CNS) HBs, endolymphatic sac tumors, pancreatic neuroendocrine tumors, pancreatic cystadenomas, pancreatic cysts, clear cell renal cell carcinomas, renal cysts, pheochromocytomas, paragangliomas, and epididymal and broad ligament cystadenomas. The VHL/hypoxia-inducible factor pathway is believed to play a key role in the pathogenesis of VHL-related tumors. The diagnosis of VHL can be made clinically when the characteristic clinical history and findings have manifested, such as the presence of two or more CNS HBs. Genetic testing for heterozygous germline VHL mutation may also be used to confirm the diagnosis of VHL. Imaging plays an important role in the diagnosis and surveillance of patients with VHL. Familiarity with the clinical and imaging manifestations of the various VHL-related tumors is important for early detection and guiding appropriate management. The purpose of this article is to discuss the molecular cytogenetics and clinical manifestations of VHL, review the characteristic multimodality imaging features of the various VHL-related tumors affecting multiple organ systems, and discuss the latest advances in management of VHL, including current recommendations for surveillance and screening

    Respiratory organ motion in interventional MRI : tracking, guiding and modeling

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    Respiratory organ motion is one of the major challenges in interventional MRI, particularly in interventions with therapeutic ultrasound in the abdominal region. High-intensity focused ultrasound found an application in interventional MRI for noninvasive treatments of different abnormalities. In order to guide surgical and treatment interventions, organ motion imaging and modeling is commonly required before a treatment start. Accurate tracking of organ motion during various interventional MRI procedures is prerequisite for a successful outcome and safe therapy. In this thesis, an attempt has been made to develop approaches using focused ultrasound which could be used in future clinically for the treatment of abdominal organs, such as the liver and the kidney. Two distinct methods have been presented with its ex vivo and in vivo treatment results. In the first method, an MR-based pencil-beam navigator has been used to track organ motion and provide the motion information for acoustic focal point steering, while in the second approach a hybrid imaging using both ultrasound and magnetic resonance imaging was combined for advanced guiding capabilities. Organ motion modeling and four-dimensional imaging of organ motion is increasingly required before the surgical interventions. However, due to the current safety limitations and hardware restrictions, the MR acquisition of a time-resolved sequence of volumetric images is not possible with high temporal and spatial resolution. A novel multislice acquisition scheme that is based on a two-dimensional navigator, instead of a commonly used pencil-beam navigator, was devised to acquire the data slices and the corresponding navigator simultaneously using a CAIPIRINHA parallel imaging method. The acquisition duration for four-dimensional dataset sampling is reduced compared to the existing approaches, while the image contrast and quality are improved as well. Tracking respiratory organ motion is required in interventional procedures and during MR imaging of moving organs. An MR-based navigator is commonly used, however, it is usually associated with image artifacts, such as signal voids. Spectrally selective navigators can come in handy in cases where the imaging organ is surrounding with an adipose tissue, because it can provide an indirect measure of organ motion. A novel spectrally selective navigator based on a crossed-pair navigator has been developed. Experiments show the advantages of the application of this novel navigator for the volumetric imaging of the liver in vivo, where this navigator was used to gate the gradient-recalled echo sequence

    NiftyNet: a deep-learning platform for medical imaging

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    Medical image analysis and computer-assisted intervention problems are increasingly being addressed with deep-learning-based solutions. Established deep-learning platforms are flexible but do not provide specific functionality for medical image analysis and adapting them for this application requires substantial implementation effort. Thus, there has been substantial duplication of effort and incompatible infrastructure developed across many research groups. This work presents the open-source NiftyNet platform for deep learning in medical imaging. The ambition of NiftyNet is to accelerate and simplify the development of these solutions, and to provide a common mechanism for disseminating research outputs for the community to use, adapt and build upon. NiftyNet provides a modular deep-learning pipeline for a range of medical imaging applications including segmentation, regression, image generation and representation learning applications. Components of the NiftyNet pipeline including data loading, data augmentation, network architectures, loss functions and evaluation metrics are tailored to, and take advantage of, the idiosyncracies of medical image analysis and computer-assisted intervention. NiftyNet is built on TensorFlow and supports TensorBoard visualization of 2D and 3D images and computational graphs by default. We present 3 illustrative medical image analysis applications built using NiftyNet: (1) segmentation of multiple abdominal organs from computed tomography; (2) image regression to predict computed tomography attenuation maps from brain magnetic resonance images; and (3) generation of simulated ultrasound images for specified anatomical poses. NiftyNet enables researchers to rapidly develop and distribute deep learning solutions for segmentation, regression, image generation and representation learning applications, or extend the platform to new applications.Comment: Wenqi Li and Eli Gibson contributed equally to this work. M. Jorge Cardoso and Tom Vercauteren contributed equally to this work. 26 pages, 6 figures; Update includes additional applications, updated author list and formatting for journal submissio

    Primary leiomyosarcoma of the pancreas: report of a case treated by local excision and review of the literature

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    First described by Ross in 1951, primary pancreatic leiomyosarcoma is a rare mesenchymal tumour of the pancreas, with nonspecific clinical and radiological features and a poor prognosis, if unresectable

    Radiological evaluation of biomarkers for renal cell carcinoma

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    Role of MRI DWI sequences in the evaluation of early response to neo- angiogenesis inhibitors in metastatic renal cell carcinoma Purpose: Angiogenesis inhibitors have a potential role in treating metastatic renal cell carcinoma, but it is still not clear why some patients don't respond. Our objective was to look for DWI parameters able to identify patients with metastatic renal cell carcinoma who would not benefit from target therapy. RECIST1.1 was considered as Reference Standard. Methods & Materials: We prospectively enrolled 43 patients candidate to start angiogenesis inhibitors with at least one target lesion and who underwent 1,5T MRI examination with multiple bvalues DWI sequences (0,40,200,300,600): one week before (t0), 2 weeks after (t2) and 8 weeks (t8) after treatment beginning. ADC value was calculated drawing ROIs on 3 different planes. 33 patients with 38 lesions had suitable data for comparative evaluation. Results: At T8 follow-up 9 patients had partial response (PR), 20 table disease (SD), 4 progression disease (PD); average progression free survival was 272 days. PD group, as compared to DC or to PR showed significantly lower ADC values at b40 at t0 (p<0.05): we can assess that more vascularised lesions are more responsive to treatment. PD group have significantly lower ADC values then both other groups, at t0, t2 and t8, for all b-values (p<0.05). PFS and OS correlates well with ADC, in particular OS with ADC b40 at t0 (r=0,69). Coclusions: Results show that PD group has significantly lower ADC values than PR or DC everytime (t0, t2, t8) At t0 there is a better correlation between PFS or OS & ADC than PFS & dimensional criteria. ADC at t0 may help selecting patients with promising good response to angiogenesis inhibitors. Moreover at t0 and at t2 ADC has the potential to select patients who wouldn't benefit from angiogenesis inhibitors Nowadays, in the era of target therapy, it is crucial to select patients potentially responders. We have to look at cost/benefit ratio and at increasing costs of treatment options. DWI has the potential role to identify patients whose's tumor wouldn't benefit from target therapy, adding a value (ADC) to other imaging (e.g. DCE-MRI, texture imaging) and clinical parameters (e.g. miRNA) in a hypothetic multiparametric analysis.CT Texture Analysis in Clear Cell Renal Cell Carcinoma: a Radiogenomics Prospective Purpose: The aim of this study was to investigate whether quantitative parameters obtained from CT Texture Analysis (CTTA) correlate with expression of miRNA in clear cell Renal Cell Carcinoma (ccRCC). Methods and Materials: In a retrospective single centre study, multiphasic CT examination (with arterial, portal, equilibrium and urographic phases) was performed on 20 patients with clear cell renal carcinomas (14 men and 6 women; mean age 65 years ± 13). Measures of heterogeneity were obtained in post-processing by placing a ROI on the entire tumour and CTTA parameters such as entropy, kurtosis, skewness, mean, mean of positive pixels, and SD of pixel distribution histogram were measured using multiple filter settings. Quantitative data were correlated with the expression of miRNAs obtained from the same cohort of patients: 8 fresh frozen samples and 12 formalin-fixed paraffin-embedded samples (miR-21-5p, miR-210-3p, miR-185-5p, miR-221-3p, miR-145-5p). Both evaluations (miRNAs and CTTA) were performed on tumour tissues as well as on normal cortico-medullar tissues. Analysis of Variance with linear multiple regression model methods were obtained with SPSS statistic software. For all comparisons, statistical significance was assumed p<0.05 Results: We evidenced that CTTA has robust parameters (e.g. entropy, mean, sd) to distinguish normal from pathological tissues. Moreover, a higher coefficient of determination between entropy and miR-21-5p expression (R2 =0,25) was evidenced in tumour tissues as compared to normal tissues (R2 =0,15). Interestingly, excluding four patients with extreme over-expression of miR-21-5p, excellent relation between entropy and miR21-5p levels was found specifically in tumour samples (R2= 0,64; p<0.05). Conclusion: Entropy and miRNA-21-5p show promising correlation in ccRCC; in addiction CTTA features, in particular mean and entropy show a statistically significant increase in ccRCC as compared with normal renal parenchyma

    Clinical value of a combined multi-phase contrast enhanced DOPA-PET/CT in neuroendocrine tumours with emphasis on the diagnostic CT component

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    Objective: To assess the clinical value of multi-phase, contrast-enhanced DOPA-PET/CT with emphasis on the diagnostic CT component in patients with neuroendocrine tumours (NET). Methods: Sixty-five patients with NET underwent DOPA-cePET/CT. The DOPA-PET, multi-phase CT and combined DOPA cePET/CT data were evaluated and diagnostic accuracies compared. The value of ceCT in DOPA cePET/CT concerning lesion detection and therapeutic impact was evaluated. Sensitivities, specificities and accuracies were calculated. Histopathology and clinical follow-up served as the standard of reference. Differences were tested for statistical significance by McNemar's test. Results: In 40 patients metastatic and/or primary tumour lesions were detected. Lesion-based analysis for the DOPA-PET showed sensitivity, specificity and accuracy of 66%, 100% and 67%, for the ceCT data 85%, 71% and 85%, and for the combined DOPA cePET/CT data 97%, 71% and 96%. DOPA cePET/CT was significantly more accurate compared with dual-phase CT (p < 0.05) and PET alone (p < 0.05). Additional lesion detection was based on ceCT in 12 patients; three patients underwent significant therapeutic changes based on the ceCT findings. Conclusion: DOPA cePET/CT was significantly more accurate than DOPA-PET alone and ceCT alone. The CT component itself had a diagnostic impact in a small percentage but contributed to the therapeutic strategies in selected patient
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