93 research outputs found
Kodierung enzymatischer Reaktionen
Die Einteilung enzymatischer Reaktionen erfolgt auf Basis des EC-Klassifikationssystems. Die Einordnung neuer Enzyme ist hochkomplex und erfordert die Absprache von verschiedenen Enzymkommissionen der Organisationen IUPAC und IUBMB. Dieses zeitaufwendige Verfahren war die Motivation fĂŒr die vorliegende Arbeit, ein automatisiertes System fĂŒr die Charakterisierung enzymatischer Reaktionen zu entwickeln, das auf dem Dugundji-Ugi-Modell basiert. Hierbei werden Reaktionen durch mathematische Operatoren beschrieben, die als Reaktionsmatrizen (R-Matrizen) bezeichnet werden und das Elektronentransfermuster einer Reaktion kodieren. R-Matrizen enthalten die Information, welche Bindungen gespalten werden oder entstehen und welche Atome an der Reaktion beteiligt sind. Das Errechnen der R-Matrizen erfordert allerdings eine Atomzuordnung der Eduktatome auf die Produktatome. Diese Zuordnung wurde in der Vergangenheit immer mit hohem manuellem Aufwand erstellt. Im Rahmen dieser Arbeit wurde ein Programm entwickelt, das die R-Matrizen nur anhand der Edukt- und ProduktmolekĂŒle errechnet und ohne manuelle UnterstĂŒtzung auskommt. Kern des Verfahrens ist ein MCS-Algorithmus (Maximal Common Subgraph), der die maximalen gemeinsamen Substrukturen von 2 MolekĂŒlen errechnet. Dieser neu entwickelte Algorithmus ist sehr flexibel und kann daher auch komplexe VerĂ€nderungen in der MolekĂŒlstruktur nachvollziehen. Er wird dazu verwendet, die EduktmolekĂŒle mit den ProduktmolekĂŒlen zu vergleichen. Die maximalen gemeinsamen Substrukturen aus den MolekĂŒlvergleichen werden kombiniert und durch ein Rankingsystem bewertet, das alle möglichen Atomzuordnungen errechnet. Bedingt durch die KomplexitĂ€t vieler biochemischer Reaktionen, war es erforderlich, das Verfahren um weitere Algorithmen zu erweitern, um falsche Zuordnungen zu vermeiden und die Laufzeit zu verbessern. So wurden Verfahren zur Erkennung von lokalen Symmetrien, aromatischen Ringsystemen und Kofaktoren integriert und eine weitere MolekĂŒlvergleichsebene eingefĂŒhrt. Mit Hilfe dieses Systems von verschiedenen Algorithmen wird eine vollstĂ€ndige Atomzuordnung generiert. Auf Grundlage einer vollstĂ€ndigen Atomzuordnung ist die Berechnung der R-Matrizen schlieĂlich sehr einfach. Ein weiteres Problem stellte allerdings der Vergleich der R-Matrizen dar, weil von jeder R-Matrix n! mögliche Permutationen erzeugt werden können. Der Vergleich erfolgt mit Hilfe eines neuen Kanonisierungsalgorithmus, der aus der Vielzahl von Permutationen eine reprĂ€sentative R-Matrix selektiert. Die ĂberfĂŒhrung der R-Matrizen in R-Strings vereinfacht schlieĂlich den Vergleich und die Gruppierung von enzymatischen Reaktionen anhand ihres Elektronentransfermusters. Auf der Grundlage eines Datensets, das 228 der 229 definierten Subsubklassen abdeckt, wurden die R-Matrizen von 3209 enzymatischen Reaktionen automatisch errechnet. Neben der Analyse der R-Matrizen selbst, standen bei der Auswertung die Beziehungen zwischen dem Dugundji-Ugi-Modell und dem EC-Klassifikationssystem im Vordergrund. Als Bezugspunkt wurden die Subsubklassen des EC-Klassifikationssystems gewĂ€hlt, die bereits soweit spezifiziert sind, dass hier eine hohe Ăbereinstimmung beider Systeme zu erwarten war. So wurden die Subsubklassen auf ihre HomogenitĂ€t in ihren Elektronentransfermustern untersucht. Die hĂ€ufigsten R-Matrizen jeder Subsubklasse wurden verglichen und Subsubklassen mit identischen R-Matrizen gruppiert. Die Elektronentransfermuster innerhalb der Subsubklassen erwiesen sich in der Mehrzahl als homogen. Allerdings wurden auch Subsubklassen mit geringer Ăbereinstimmung in den Elektronentransfermustern gefunden, fĂŒr die eine höhere HomogenitĂ€t erwartet worden wĂ€re. Der R-Matrixvergleich der verschiedenen Subsubklassen ergab, dass 121 Subsubklassen bereits ein spezifisches Elektronentransfermuster besitzen. 107 Subsubklassen bilden hingegen Gruppen verschiedener GröĂe. Einige Gruppen bestehen aus Subsubklassen von verschiedenen Hauptklassen, obwohl sie nach ihren Elektronentransfermustern einen identischen Reaktionskern besitzen. Die Ergebnisse machen die Eigenschaften des Dugundji-Ugi-Modells deutlich, das sehr rational und unvoreingenommen die wesentlichsten Eigenschaften einer Reaktion beschreibt. Ăhnlich, wie das EC-Klassifikationssystem, betrachtet es aber die chemischen Eigenschaften der Gesamtreaktion. Es könnte daher die Enzymklassifikation unterstĂŒtzen, indem es aufzeigt, welche Subsubklassen feiner untergliedert oder zu gröĂeren Gruppen zusammengefasst werden könnten
Assessment of atherosclerotic carotid plaque volume with multidetector computed tomography angiography
Purpose The amount of atherosclerotic plaque and its components (calcifications, fibrous tissue, and lipid core) could be better predictors of acute events than the now currently used degree of stenosis. Therefore, we evaluated a dedicated software tool for volume measurements of atherosclerotic carotid plaque and its components in multidetector computed tomography angiography (MDCTA) images. Materials and Methods Data acquisition was approved by the Institutional Review Board and all patients gave written informed consent. MDCTA images of 56 carotid arteries were analyzed by three observers. Plaque volumes were assessed by manual drawing of the outer vessel contour. The luminal boundary was determined based on a Hounsfield-Unit (HU) threshold. The contribution of different components was measured by the number of voxels within defined ranges of HU-values (calcification >130 HU, fibrous tissue 60â130 HU, lipid core <60 HU). Interobserver variability (IOV) was assessed. Results Plaque volume was 1,259 ± 621 mm3. The calcified, fibrous and lipid volumes were 238 ± 252 mm3, 647 ± 277 mm3 and 376 ± 283 mm3, respectively. IOV was moderate with interclass correlation coefficients (ICC) ranging from 0.76 to 0.99 and coefficients of variation (COV) ranging from 3% to 47%. Conclusion Atherosclerotic carotid plaque volume and plaque component volumes can be assessed with MDCTA with a reasonable observer variability
Follow-up of loci from the International Genomics of Alzheimer's Disease Project identifies TRIP4 as a novel susceptibility gene
To follow-up loci discovered by the International Genomics of Alzheimer's Disease Project, we attempted independent replication of 19 single nucleotide polymorphisms (SNPs) in a large Spanish sample (FundaciĂł ACE data set; 1808 patients and 2564 controls). Our results corroborate association with four SNPs located in the genes INPP5D, MEF2C, ZCWPW1 and FERMT2, respectively. Of these, ZCWPW1 was the only SNP to withstand correction for multiple testing (P=0.000655). Furthermore, we identify TRIP4 (rs74615166) as a novel genome-wide significant locus for Alzheimer's disease risk (odds ratio=1.31; confidence interval 95% (1.19-1.44); P=9.74 Ă 10 - 9)
FachkrÀftebedarf: Analyse und Handlungsstrategien
Mit der verbesserten Lage am Arbeitsmarkt und dem aus demografischen GrĂŒnden zu erwartenden RĂŒckgang des Erwerbspersonenpotenzials gewinnt auch das Thema FachkrĂ€ftesicherung immer mehr an Bedeutung. Dieses Thema wird in Kapitel D ("FachkrĂ€ftebedarf: Analyse und Handlungsstrategien") eingehend behandelt. Dabei wird deutlich: Die Folgen des demografischen Wandels fĂŒr den Arbeitsmarkt sind erheblich und es muss an vielen Stellschrauben gedreht werden, um diese abzumildern. Sowohl die Mobilisierung inlĂ€ndischer Potenziale als auch die verstĂ€rkte Zuwanderung von FachkrĂ€ften ist notwendig, um den RĂŒckgang des Erwerbspotenzials spĂŒrbar abzufedern
Genome-wide meta-analyses reveal novel loci for verbal short-term memory and learning
Understanding the genomic basis of memory processes may help in combating neurodegenerative disorders. Hence, we examined the associations of common genetic variants with verbal short-term memory and verbal learning in adults without dementia or stroke (N = 53,637). We identified novel loci in the intronic region of CDH18, and at 13q21 and 3p21.1, as well as an expected signal in the APOE/APOC1/TOMM40 region. These results replicated in an independent sample. Functional and bioinformatic analyses supported many of these loci and further implicated POC1. We showed that polygenic score for verbal learning associated with brain activation in right parieto-occipital region during working memory task. Finally, we showed genetic correlations of these memory traits with several neurocognitive and health outcomes. Our findings suggest a role of several genomic loci in verbal memory processes.Peer reviewe
Genome-wide association analysis of genetic generalized epilepsies implicates susceptibility loci at 1q43, 2p16.1, 2q22.3 and 17q21.32
Genetic generalized epilepsies (GGEs) have a lifetime prevalence of 0.3% and account for 20-30% of all epilepsies. Despite their high heritability of 80%, the genetic factors predisposing to GGEs remain elusive. To identify susceptibility variants shared across common GGE syndromes, we carried out a two-stage genome-wide association study (GWAS) including 3020 patients with GGEs and 3954 controls of European ancestry. To dissect out syndrome-related variants, we also explored two distinct GGE subgroups comprising 1434 patients with genetic absence epilepsies (GAEs) and 1134 patients with juvenile myoclonic epilepsy (JME). Joint Stage-1 and 2 analyses revealed genome-wide significant associations for GGEs at 2p16.1 (rs13026414, Pmeta = 2.5 Ă 10â9, OR[T] = 0.81) and 17q21.32 (rs72823592, Pmeta = 9.3 Ă 10â9, OR[A] = 0.77). The search for syndrome-related susceptibility alleles identified significant associations for GAEs at 2q22.3 (rs10496964, Pmeta = 9.1 Ă 10â9, OR[T] = 0.68) and at 1q43 for JME (rs12059546, Pmeta = 4.1 Ă 10â8, OR[G] = 1.42). Suggestive evidence for an association with GGEs was found in the region 2q24.3 (rs11890028, Pmeta = 4.0 Ă 10â6) nearby the SCN1A gene, which is currently the gene with the largest number of known epilepsy-related mutations. The associated regions harbor high-ranking candidate genes: CHRM3 at 1q43, VRK2 at 2p16.1, ZEB2 at 2q22.3, SCN1A at 2q24.3 and PNPO at 17q21.32. Further replication efforts are necessary to elucidate whether these positional candidate genes contribute to the heritability of the common GGE syndrome
Gene set enrichment analysis and expression pattern exploration implicate an involvement of neurodevelopmental processes in bipolar disorder
Background Bipolar disorder (BD) is a common and highly heritable disorder of mood. Genome-wide association studies (GWAS) have identified several independent susceptibility loci. In order to extract more biological information from GWAS data, multi-locus approaches represent powerful tools since they utilize knowledge about biological processes to integrate functional sets of genes at strongly to moderately associated loci. Methods We conducted gene set enrichment analyses (GSEA) using 2.3 million single-nucleotide polymorphisms, 397 Reactome pathways and 24,025 patients with BD and controls. RNA expression of implicated individual genes and gene sets were examined in post-mortem brains across lifespan. Results Two pathways showed a significant enrichment after correction for multiple comparisons in the GSEA: GRB2 events in ERBB2 signaling, for which 6 of 21 genes were BD associated (P = 0.0377), and NCAM signaling for neurite out-growth, for which 11 out of 62 genes were BD associated (P = 0.0451). Most pathway genes showed peaks of RNA co-expression during fetal development and infancy and mapped to neocortical areas and parts of the limbic system. Limitations Pathway associations were technically reproduced by two methods, although they were not formally replicated in independent samples. Gene expression was explored in controls but not in patients. Conclusions Pathway analysis in large GWAS data of BD and follow-up of gene expression patterns in healthy brains provide support for an involvement of neurodevelopmental processes in the etiology of this neuropsychiatric disease. Future studies are required to further evaluate the relevance of the implicated genes on pathway functioning and clinical aspects of BD
Gene set enrichment analysis and expression pattern exploration implicate an involvement of neurodevelopmental processes in bipolar disorder
Bipolar disorder (BD) is a common and highly heritable disorder of mood. Genome-wide association studies (GWAS) have identified several independent susceptibility loci. In order to extract more biological information from GWAS data, multi-locus approaches represent powerful tools since they utilize knowledge about biological processes to integrate functional sets of genes at strongly to moderately associated loci.We conducted gene set enrichment analyses (GSEA) using 2.3 million single-nucleotide polymorphisms, 397 Reactome pathways and 24,025 patients with BD and controls. RNA expression of implicated individual genes and gene sets were examined in post-mortem brains across lifespan.Two pathways showed a significant enrichment after correction for multiple comparisons in the GSEA: GRB2 events in ERBB2 signaling, for which 6 of 21 genes were BD associated (PFDR = 0.0377), and NCAM signaling for neurite out-growth, for which 11 out of 62 genes were BD associated (PFDR = 0.0451). Most pathway genes showed peaks of RNA co-expression during fetal development and infancy and mapped to neocortical areas and parts of the limbic system.Pathway associations were technically reproduced by two methods, although they were not formally replicated in independent samples. Gene expression was explored in controls but not in patients.Pathway analysis in large GWAS data of BD and follow-up of gene expression patterns in healthy brains provide support for an involvement of neurodevelopmental processes in the etiology of this neuropsychiatric disease. Future studies are required to further evaluate the relevance of the implicated genes on pathway functioning and clinical aspects of BD
Proceedings of the International Cancer Imaging Society (ICIS) 16th Annual Teaching Course
Table of contents
O1 Tumour heterogeneity: what does it mean?
Dow-Mu Koh
O2 Skeletal sequelae in adult survivors of childhood cancer
Sue Creviston Kaste
O3 Locoregional effects of breast cancer treatment
Sarah J Vinnicombe
O4 Imaging of cancer therapy-induced CNS toxicity
Giovanni Morana, Andrea Rossi
O5 Screening for lung cancer
Christian J. Herold
O6Risk stratification of lung nodules
Theresa C. McLoud
O7 PET imaging of pulmonary nodules
Kirk A Frey
O8 Transarterial tumour therapy
Bernhard Gebauer
O9 Interventional radiology in paediatric oncology
Derek Roebuck
O10 Image guided prostate interventions
Jurgen J. FĂŒtterer
O11 Imaging cancer predisposition syndromes
Alexander J. Towbin
O12Chest and chest wall masses
Thierry AG Huisman
O13 Abdominal masses: good or bad?
Anne MJB Smets
O14 Hepatobiliary MR contrast: enhanced liver MRI for HCC diagnosis and management
Giovanni Morana
O15 Role of US elastography and multimodality fusion for managing patients with chronic liver disease and HCC
Jeong Min Lee
O16 Opportunities and challenges in imaging metastatic disease
Hersh Chandarana
O17 Diagnosis, treatment monitoring, and follow-up of lymphoma
Marius E. Mayerhoefer, Markus Raderer, Alexander Haug
O18 Managing high-risk and advanced prostate cancer
Matthias Eiber
O19 Immunotherapy: imaging challenges
Bernhard Gebauer
O20 RECIST and RECIST 1.1
Andrea Rockall
O21 Challenges of RECIST in oncology imaging basics for the trainee and novice
Aslam Sohaib
O22 Lymphoma: PET for interim and end of treatment response assessment: a usersâ guide to the Deauville Score
Victoria S Warbey
O23 Available resources
Hebert Alberto Vargas
O24 ICIS e-portal and the online learning community
Dow-Mu Koh
O25 Benign lesions that mimic pancreatic cancer
Jay P Heiken
O26 Staging and reporting pancreatic malignancies
Isaac R Francis, Mahmoud, M Al-Hawary, Ravi K Kaza
O27 Intraductal papillary mucinous neoplasm
Giovanni Morana
O28 Cystic pancreatic tumours
Mirko DâOnofrio
O29 Diffusion-weighted imaging of head and neck tumours
Harriet C. Thoeny
O30 Radiation injury in the head and neck
Ann D King
O31 PET/MR of paediatric brain tumours
Giovanni Morana, Arnoldo Piccardo, Maria Luisa GarrĂš, Andrea Rossi
O32 Structured reporting and beyond
Hebert Alberto Vargas
O33 Massachusetts General Hospital experience with structured reporting
Theresa C. McLoud
O34 The oncologistâs perspective: what the oncologist needs to know
Nick Reed
O35 Towards the cure of all children with cancer: global initiatives in pediatric oncology
Carlos Rodriguez-Galindo
O36 Multiparametric imaging of renal cancers
Hersh Chandarana
O37 Linking imaging features of renal disease and their impact on management strategies
Hebert Alberto Vargas
O38 Adrenals, retroperitoneum and peritoneum
Isaac R Francis, Ashish P Wasnik
O39 Lung and pleura
Stefan Diederich
O40 Advances in MRI
Jurgen J. FĂŒtterer
O41 Advances in molecular imaging
Wim J.G. Oyen
O42 Incorporating advanced imaging, impact on treatment selection and patient outcome
Cheng Lee Chaw, Nicholas van As
S1 Combining ADC-histogram features improves performance of MR diffusion-weighted imaging for Lymph node characterisation in cervical cancer
Igor Vieira, Frederik De Keyzer, Elleke Dresen, Sileny Han, Ignace Vergote, Philippe Moerman, Frederic Amant, Michel Koole, Vincent Vandecaveye
S2 Whole-body diffusion-weighted MRI for surgical planning in patients with colorectal cancer and peritoneal metastases
R Dresen, S De Vuysere, F De Keyzer, E Van Cutsem, A DâHoore, A Wolthuis, V Vandecaveye
S3 Role of apparent diffusion coefficient (ADC) diffusion-weighted MRI for predicting extra capsular extension of prostate cancer.
P. Pricolo ([email protected]), S. Alessi, P. Summers, E. Tagliabue, G. Petralia
S4 Generating evidence for clinical benefit of PET/CT â are management studies sufficient as surrogate for patient outcome?
C. Pfannenberg, B. GĂŒckel, SC SchĂŒle, AC MĂŒller, S. Kaufmann, N. Schwenzer, M. Reimold,C. la Fougere, K. Nikolaou, P. Martus
S5 Heterogeneity of treatment response in skeletal metastases from breast cancer with 18F-fluoride and 18F-FDG PET
GJ Cook, GK Azad, BP Taylor, M Siddique, J John, J Mansi, M Harries, V Goh
S6 Accuracy of suspicious breast imagingâcan we tell the patient?
S Seth, R Burgul, A Seth
S7 Measurement method of tumour volume changes during neoadjuvant chemotherapy affects ability to predict pathological response
S Waugh, N Muhammad Gowdh, C Purdie, A Evans, E Crowe, A Thompson, S Vinnicombe
S8 Diagnostic yield of CT IVU in haematuria screening
F. Arfeen, T. Campion, E. Goldstraw
S9 Percutaneous radiofrequency ablation of unresectable locally advanced pancreatic cancer: preliminary results
DâOnofrio M, Ciaravino V, Crosara S, De Robertis R, Pozzi Mucelli R
S10 Iodine maps from dual energy CT improve detection of metastases in staging examinations of melanoma patients
M. Uhrig, D. Simons, H. Schlemmer
S11Can contrast enhanced CT predict pelvic nodal status in malignant melanoma of the lower limb?
Kate Downey
S12 Current practice in the investigation for suspected Paraneoplastic Neurological Syndromes (PNS) and positive malignancy yield.
S Murdoch, AS Al-adhami, S Viswanathan
P1 Technical success and efficacy of Pulmonary Radiofrequency ablation: an analysis of 207 ablations
S Smith, P Jennings, D Bowers, R Soomal
P2 Lesion control and patient outcome: prospective analysis of radiofrequency abaltion in pulmonary colorectal cancer metastatic disease
S Smith, P Jennings, D Bowers, R Soomal
P3 Hepatocellular carcinoma in a post-TB patient: case of tropical infections and oncologic imaging challenges
TM Mutala, AO Odhiambo, N Harish
P4 Role of apparent diffusion coefficient (ADC) diffusion-weighted MRI for predicting extracapsular extension of prostate cancer
P. Pricolo, S. Alessi, P. Summers, E. Tagliabue, G. Petralia
P5 What a difference a decade makes; comparison of lung biopsies in Glasgow 2005 and 2015
M. Hall, M. Sproule, S. Sheridan
P6 Solid pseudopapillary tumour of pancreas: imaging features of a rare neoplasm
KY Thein, CH Tan, YL Thian, CM Ho
P7 MDCT - pathological correlation in colon adenocarcinoma staging: preliminary experience
S De Luca, C Carrera, V Blanchet, L AlarcĂłn, E Eyheremnedy
P8 Image guided biopsy of thoracic masses and reduction of pneumothorax risk: 25Â years experience
B K Choudhury, K Bujarbarua, G Barman
P9 Tumour heterogeneity analysis of 18F-FDG-PET for characterisation of malignant peripheral nerve sheath tumours in neurofibromatosis-1
GJ Cook, E Lovat, M Siddique, V Goh, R Ferner, VS Warbey
P10 Impact of introduction of vacuum assisted excision (VAE) on screen detected high risk breast lesions
L Potti, B Kaye, A Beattie, K Dutton
P11 Can we reduce prevalent recall rate in breast screening?
AA Seth, F Constantinidis, H Dobson
P12 How to reduce prevalent recall rate? Identifying mammographic lesions with low Positive Predictive Value (PPV)
AA Seth ([email protected]), F Constantinidis, H Dobson
P13 Behaviour of untreated pulmonary thrombus in oncology patients diagnosed with incidental pulmonary embolism on CT
R. Bradley, G. Bozas, G. Avery, A. Stephens, A. Maraveyas
P14 A one-stop lymphoma biopsy service â is it possible?
S Bhuva, CA Johnson, M Subesinghe, N Taylor
P15 Changes in the new TNM classification for lung cancer (8th edition, effective January 2017)
LE Quint, RM Reddy, GP Kalemkerian
P16 Cancer immunotherapy: a review of adequate imaging assessment
G GonzĂĄlez Zapico, E Gainza Jauregui, R Ălvarez Francisco, S Ibåñez Alonso, I Tavera Bahillo, L MĂșgica Ălvarez
P17 Succinate dehydrogenase mutations and their associated tumours
O Francies, R Wheeler, L Childs, A Adams, A Sahdev
P18 Initial experience in the usefulness of dual energy technique in the abdomen
SE De Luca, ME Casalini Vañek, MD Pascuzzi, T Gillanders, PM Ramos, EP Eyheremendy
P19 Recognising the serious complication of Richterâs transformation in CLL patients
C Stove, M Digby
P20 Body diffusion-weighted MRI in oncologic practice: truths, tricks and tips
M. Nazar, M. Wirtz, MD. Pascuzzi, F. Troncoso, F. Saguier, EP. Eyheremendy
P21 Methotrexate-induced leukoencephalopathy in paediatric ALL Patients
D.J. Quint, L. Dang, M. Carlson, S. Leber, F. Silverstein
P22 Pitfalls in oncology CT reporting. A pictorial review
R Rueben, S Viswanathan
P23 Imaging of perineural extension in head and neck tumours
B Nazir, TH Teo, JB Khoo
P24 MRI findings of molecular subtypes of breast cancer: a pictorial primer
K Sharma, N Gupta, B Mathew, T Jeyakumar, K Harkins
P25 When cancer canât wait! A pictorial review of oncological emergencies
K Sharma, B Mathew, N Gupta, T Jeyakumar, S Joshua
P26 MRI of pancreatic neuroendocrine tumours: an approach to interpretation
D Christodoulou, S Gourtsoyianni, A Jacques, N Griffin, V Goh
P27 Gynaecological cancers in pregnancy: a review of imaging
CA Johnson, J Lee
P28 Suspected paraneoplastic neurological syndromes - review of published recommendations to date, with proposed guideline/flowchart
JA Goodfellow, AS Al-adhami, S Viswanathan
P29 Multi-parametric MRI of the pelvis for suspected local recurrence of prostate cancer after radical prostatectomy
R Bradley
P30 Utilisation of PI-RADS version 2 in multi-parametric MRI of the prostate; 12-months experience
R Bradley
P31 Radiological assessment of the post-chemotherapy liver
A Yong, S Jenkins, G Joseph
P32 Skeletal staging with MRI in breast cancer â what the radiologist needs to know
S Bhuva, K Partington
P33 Perineural spread of lympoma: an educational review of an unusual distribution of disease
CA Johnson, S Bhuva, M Subesinghe, N Taylor
P34 Visually isoattenuating pancreatic adenocarcinoma. Diagnostic imaging tools.
C Carrera, A Zanfardini, S De Luca, L AlarcĂłn, V Blanchet, EP Eyheremendy
P35 Imaging of larynx cancer: when is CT, MRI or FDG PET/CT the best test?
K Cavanagh, E Lauhttp://deepblue.lib.umich.edu/bitstream/2027.42/134651/1/40644_2016_Article_79.pd
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