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45 results on '"Bronstein M"'

1. Weisfeiler and Lehman Go Cellular: CW Networks

Author

Bodnar, C., Frasca, F., Otter, N., Wang, Y. G., Pietro Lio, Montúfar, G., and Bronstein, M.

Subjects
FOS: Computer and information sciences, Computer Science - Machine Learning, Statistics - Machine Learning, Machine Learning (stat.ML), Machine Learning (cs.LG)
Abstract

Graph Neural Networks (GNNs) are limited in their expressive power, struggle with long-range interactions and lack a principled way to model higher-order structures. These problems can be attributed to the strong coupling between the computational graph and the input graph structure. The recently proposed Message Passing Simplicial Networks naturally decouple these elements by performing message passing on the clique complex of the graph. Nevertheless, these models can be severely constrained by the rigid combinatorial structure of Simplicial Complexes (SCs). In this work, we extend recent theoretical results on SCs to regular Cell Complexes, topological objects that flexibly subsume SCs and graphs. We show that this generalisation provides a powerful set of graph "lifting" transformations, each leading to a unique hierarchical message passing procedure. The resulting methods, which we collectively call CW Networks (CWNs), are strictly more powerful than the WL test and not less powerful than the 3-WL test. In particular, we demonstrate the effectiveness of one such scheme, based on rings, when applied to molecular graph problems. The proposed architecture benefits from provably larger expressivity than commonly used GNNs, principled modelling of higher-order signals and from compressing the distances between nodes. We demonstrate that our model achieves state-of-the-art results on a variety of molecular datasets., NeurIPS 2021. Contains 28 pages, 9 figures

Published
2021

2. Graph attentional autoencoder for anticancer hyperfood prediction

Author

Gonzalez, G, Gong, S, Laponogov, I, Veselkov, K, Bronstein, M, and The Vodafone Foundation

Subjects
cs.LG, natural sciences, cs.AI
Abstract

Recent research efforts have shown the possibility to discover anticancer drug-like molecules in food from their effect on protein-protein interaction networks, opening a potential pathway to disease-beating diet design. We formulate this task as a graph classification problem on which graph neural networks (GNNs) have achieved state-of-the-art results. However, GNNs are difficult to train on sparse low-dimensional features according to our empirical evidence. Here, we present graph augmented features, integrating graph structural information and raw node attributes with varying ratios, to ease the training of networks. We further introduce a novel neural network architecture on graphs, the Graph Attentional Autoencoder (GAA) to predict food compounds with anticancer properties based on perturbed protein networks. We demonstrate that the method outperforms the baseline approach and state-of-the-art graph classification models in this task.

Published
2020

3. SHREC’19: shape correspondence with isometric and non-isometric deformations

Author

Dyke, R. M., Stride, C., Lai, Y. -K., Rosin, P. L., Aubry, M., Boyarski, A., Bronstein, A. M., Bronstein, M. M., Cremers, D., Fisher, M., Groueix, T., Guo, D., Kim, V. G., Kimmel, R., Lähner, Z., Li, K., Litany, O., Remez, T., Rodolà, E., Russell, B. C., Sahillioglu, Y., Slossberg, R., Tam, G. K. L., Vestner, M., and and Yang, Z.

Subjects
shape correspondence, isometric and non-isometric deformations
Published
2019

4. Liraglutide and Renal Outcomes in Type 2 Diabetes

Author

Mann JFE, Ørsted DD, Brown-Frandsen K, Marso SP, Poulter NR, Rasmussen S, Tornøe K, Zinman B, Buse JB, LEADER Steering Committee and Investigators. Bergenstal R, Daniels G, Moses AC, Nauck M, Nissen S, Pocock S, Steinberg W, Stockner M, Kristensen P, Ravn LS, Zychma M, Flyvbjerg A, Ford I, Kloos RT, Schactman MJ, Sleight P, Swedberg K, Tenner SM, Akalın S, Arechavaleta R, Bain S, Babkowski MC, Benroubi M, Berard L, Comlekci A, Czupryniak L, Eliasson B, Eriksson M, Fonseca V, Franek E, Gross J, Hafidh K, Haluzik M, Hayes F, Huang YY, Jacob S, Kaddaha G, Khalil A, Kilhovd B, Laakso M, Leiter L, Lalic N, Ji L, Luedemann J, Mannucci E, Marre M, Masmiquel L, Mota M, Omar M, O’Shea D, Pan C, Petrie J, Pieber T, Pratley R, Raz I, Rea R, Rutten G, Satman I, Shestakova M, Simpson R, Smith D, Tack C, Tarnow L, Thomas N, Van Gaal L, Travert F, Vidal J, Warren M, Yoon KH, Tuttle RM, Sheerman SI, Hegedüs L, Baerwald H, Bergenstal M, Celik S, Dias C, Eder M, Fitzgibbons S, Irvhage L, Kloluckova J, Kriulianski R, McDuffie R, Moen S, Paster A, Saalfeld RM, Sankar K, Shehaj E, Swierzewska P, Tiktin M, Tovey S, Gibson CM, Chakrabarti AK, Dashe JF, Hinchey J, Leary MC, Pride Y, Wiviott S, Allen S, Mehr AP, Mutter WP, Parikh S, Ray S, Cheifetz A, Leffler D, Sheth S, Alexander E, Gaglia JL, Goessling W, Mitzner LD, Rosenberg C, Snow KJ, Wagner A, Piazza G, Abell S, Davis T, D'Emden M, Ding SA, Gilfillan C, Greenaway T, Gunawan F, Ho J, Jackson R, Kalra B, Lau SL, Lin J, MacIsaac R, Makepeace A, Malabu U, Marjason J, McCallum R, McLean M, Moin N, Petersons C, Price S, Roberts A, Roberts D, Sangla K, Stranks S, Tan Y, Thynne T, Walters J, Ward G, Wen W, Zhang J, Brix J, Feder A, Höbaus C, Höllerl F, Höller V, Kotter T, Kratz E, Krzizek EC, Leb-Stoeger U, Mader J, Mras N, Novak E, Obendorf F, Peric S, Pesau G, Prager R, Ribitsch A, Schnack C, Schernthaner G, Wascher T, Batens AH, Benhalima K, De Block C, Ernest P, Fouckova A, Jandrain B, Lapauw B, Letiexhe M, Mathieu C, Neven S, Peiffer F, Ruige J, Scheen A, Taes Y, Van Boxelaer I, Vandistel G, Van Durme Y, Verhaegen A, Alencar E, Alencar R, Almeida AC, Alves B, Alves E, Alves G, Alves J, Araujo L, Arruda V, Augusto GA, Baggentoss R, Balestrassi L, Barbosa M, Barcelos I, Belem L, de Bem A, Betti RT, Bona R, Bosco A, Branda J, Bronstein M, Bueno T, Bulcão T, Caiado F, Camazzola F, Cambréa MF, Campos S, Canani L, Carra MK, Caruso S, Carvalho N, Casillo A, Castro D, Cavalcanti T, Cavichioli V, Cercato C, Chacra A, Challela W, Charchar HS, Chaves C, Chrisman C, Correia-Deur J, da Costa A Jr, Costa M, Costi B, Coutinho P, Coutinho W, Cunha MR, Daher J Jr, Davini E, Democh D Jr, Eliaschewitz F, Esmanhoto Facin G, Farias F, Felício J, Fernandes V, Filho CS, Filho FF, Filho M, Fontan D, Fontenele AP, Forti A, Franco D, Freire K, Fusaro A, Genestreti P, Gerchman F, Godi A, Gomes KF, Gonçalves P, Gonçalves R, Griz L, Grossman M, Gurgel MH, Vasconcellos Haddad AW, Halpern A, Hissa M, Inuy A, Jaime J, Jonasson T, Jorge JC, Malucelli FJ, Kohara S, Kramer C, Lacerda C, Ladeira S, Lana J, Lastebasse F, Leitão A, Leite S, Lerário AC, Lima D, Lima M, Lippi V, Lunardi M, Machado E, Maia F, Maia J, Maia KP, Mañas N, Marchisotti F, Marinho C, Martins C, Figueiredo de Medeiros F, Melo A, Melo F, Mendonca E, Mendonça P, Filho RM, Miguel M, Miléo K, Miyahara M, Montenegro AP, Moraes A, Moreira A, Ítalo Mota J, Mothe FS, Murro A, Nakatani V, Napoli TF, Neto BG, Neto OQ, Niclewicz E, Ohe LN, Oliveira F, Oliveira M, Panarotto D, Parente E, Parolin S, Pechmann L, Costa da Penha P, Perlamagna L, Perotta B, Pimentel L, Pinto M, Poço C, Ponte C, Prazeres P, Quintao E, Raduan R, Rassi DT, Rassi N, Reck L, Montenegro R Jr, Ribeiro R, Rodovalho S, Silveira Rodrigues G, Rollin G, Rossi S, Sabino C, Sales AP, Salles J, Sampaio CR, Santana L, Sato V, da Silva Santos M, Santos NL, Santos R, Saraiva J, Sartori C, Sena R, Sevilha M, Sgarbi J, Silva D, D'albuquerque Silva L, Silva ME, Siqueira K, Soares S, Sobreira W, Sousa B, Souza AC, Souza B, Tambascia M, Tarantino R, Tenor F, Tomarchio M, Triches C, Tristão LJ, Valenti A, Vasques E, Vencio S, Vianna A, Munhoz Vidotto T, Vieira S, Villar H, Visconti G, Volaco A, Wajchenberg B, Zanatta L, Zimmerman L, Abbott EC, Abu-Bakare A, Advani A, Allison R, Bishara P, Bowering CK, Cheng A, Chouinard S, Clayton D, Conway J, D'Amours M, de Tugwell B, DeYoung P, D'Ignazio G, Dube F, Ekoe JM, Fagan S, Garceau C, Gottesman I, Hanna A, Harris S, Hramiak IM, Hurd C, Imran S, Josse R, Joyce C, Kaiser S, Khan F, Kirouac I, Kovacs C, Labonte I, Langlois WJ, Levac MF, Liutkus J, McDonald C, Milosevic V, Nyomba BL, Paul T, Raby K, Ransom T, Reichert SM, Retnakaran R, Rabasa-Lhoret R, Raff E, Shaikholeslami R, Sigalas J, Yip CE, Weisnagel SJ, Woo V, Bao Y, Cai X, Chen J, Chen K, Chen M, Chen X, Chen Y, Ji Y, Lei J, Li H, Liu P, Mu Y, Ren M, Ren Y, Shi Y, Wang D, Wang F, Wang J, Wang Y, Yan L, Yang G, Yang J, Yu X, Yuan G, Xu M, Zhao X, Zheng J, Zhou L, Anderlová K, Brožová J, Haluzík M, Hanušová V, Kosák M, Křížová J, Mráz M, Owen K, Rušavý Z, Tomešová J, Trachta P, Žourek M, Andersen PH, Boesgaard T, Christensen S, Gram J, Gregersen S, Henriksen JE, Hermansen K, Jakobsen PE, Jensen J, Krogsaa A, Larsen M, Lervang HH, Madsbad S, Mortensen L, Olesen T, Pietraszek A, Ridderstråle M, Safai N, Schioldan AG, Schmidt C, Snorgaard O, Stidsen J, Cederberg H, Haapamäki H, Hukkanen J, Jauhiainen R, Kujari ML, Lahtela J, Laine M, Mäkelä J, Miilunpohja M, Savolainen M, Taurio J, Vänttinen M, Creton C, Cosma NV, Dillinger J, Jacques JL, Guedj AM, Moulla M, Petit C, Ratsianoharana V, Richter D, Rodier M, Roussel R, Hinz A, Politz E, Esser M, Deuse U, Mittag D, Hagenow A, Jacob F, Jordan R, Gantke D, Venschott-Jordan U, Löhr C, Klausmann G, Eschenbrücher K, Karakas M, Jahrsdörfer B, Kunze MR, Wöhrle J, König W, Spielhagen H, Kilimnik A, Lüdemann HP, Lüdemann J, Mölle A, Mölle M, Müller J, Appelt S, Sauter A, Sauter J, Hartmann U, Löw A, Krötz F, Sohn HY, von Schacky C, Klauss V, Braun D, Segner A, Degtyareva E, Kreutzmann K, Paschmionka R, Hauck N, Sihal O, Busch AK, Maus O, Stübler P, Füllgraf-Horst S, Vietzke A, Müller C, Tosch-Sisting R, Lengsfeld B, Thaler J, Schaum T, Steindorf J, Steindorf S, König A, Reitschuster S, Schlott D, Clever HU, Witzel P, Kempe HP, Stemler L, Benis A, Diakoumopoulou E, Kazakos K, Kypraios N, Liatis S, Pagkalos E, Siami E, Tentolouris N, Alur VC, Agrawal M, Ali M, Asirvatham A, Asirvatham E, Bandgar TR, Balaji M, Bardoloi N, Baruah M, Bekur R, Bhansali A, Bhatia S, Bhonsley S, Bhuyan S, Borah B, Bright N, Ambrish C, Chaudhury T, Choudhury S, Chellan G, Das M, Dharmalingam M, Dutta P, Erugu A, Vinutha FP, Gunasekaran P, Das Gupta R, Iqbal A, Jagadish P, Jain S, Jebasingh H, John A, John M, Kalra S, Kasaragod P, Kesavadev J, Kumar H, Kumar P, Lakshmanan V, Lila AR, Mathew T, Miyen H, Mohan T, Motha A, Murthy C, Shivashankara N, Nanaiah A, Ommen T, Pani K, Pandey K, Paramesh S, Paramesh V, Pillai B, Prabhu M, Kalki RC, Ramachandran S, Ramu M, Rao Y, Reddy S, Saikia P, Saravu K, Selvam K, Sethi B, Shankar A, Sharma A, Shah N, Shankar P, Shetty R, Shivane V, Srivalli S, Thaseen S, Sarada S, Shirisha A, Subramani M, Balaji V, Mohan V, Padmanaban V, Verma M, Vidyasagar S, Walinjkar V, Walia R, Davenport C, Forde H, Gadintshware G, Gan KJ, Khattak A, O'Connell J, O'Shea D, Beilin V, Cahn A, Cohen O, Cukierman-Yaffe T, Daoud D, Darawsha M, Dicker D, Gavish A, Hochberg I, Ilany J, Inbal U, Itzhak B, Karasik A, Karnieli E, Khader N, Khamaisi M, Lender D, Lieberman GS, Mahamid R, Marcoviciu D, Michael L, Minuchin O, Mosenzon O, Narevichius F, Percik R, Potekhin M, Sabbah M, Sawaed S, Schurr D, Segal E, Slezak L, Vollach I, Zaina A, Zloczower M, Zolotov S, Antenore A, Arnone M, Arturi F, Barbaro V, Barone M, Di Biagio R, Buscemi C, Buscemi S, Buzzetti R, Di Carlo A, Carlone A, Caruso V, Casadidio I, Cerrelli F, Ciavarella A, Cipolloni L, Colella A, Colotto M, Consoli A, Crippa VG, Cuccuru I, Cufone S, Desideri C, Fallarino M, Febo F, Filetti S, Foffi C, Formoso G, Frosio L, Di Fulvio P, Gambineri A, Ginestra F, Grimaldi MS, Lamanna C, Leto G, Lucotti P, Lugarà M, Lumera G, Magistro A, Maranghi M, Martelli D, Mattina A, Monti LD, Parise M, Pedace E, Perticone F, Piatti P, Pompea Antonia Baldassarre M, Ragghianti B, Repaci A, Ribichini D, Da Ros S, Rossi M, Santilli M, Sesti G, Setola E, Succurro E, Sussolano E, Tarquini G, Verga S, Vitale V, Alanis RR, del Rosario Arechavaleta-Granell M, de Jesús Beltran Jaramillo T, de Jesús Rodríguez Berrones DA, Rodríguez Briones I, Rodríguez Briones R, Acevedo Castañeda ES, Chapa Grimaldo JB, Flores-Moreno CA, Garza Felix S, Nieto Flores J, Morales Franco G, Garza Morán RA, Hernández González SO, González-Gálvez G, González González JG, Hernández Salazar E, García Hernández PA, Campos Hurtado S, López-Velázco ML, Cardona Muñóz EG, Nuñez Márquez R, Campos Moreno OV, Cavazos Oliveros FJ, Haro Ortiz JA, Pelayo-Orozco ES, Sida Perez P, Vazquez Ramírez R, Uribe Rios MA, López Rodríguez JC, Rodríguez Rosales M, Robledo Durón I, Alvarado Ruíz R, González Saldivar G, Reyes Sánchez R, Sánchez-Michel BL, Contreras Sandoval AY, Velasco Gutiérrez A, Perez Verdín AE, Ramos Zavala MG, Abbink-Zandbergen E, Ahdi M, Bugter A, van Dijk M, Eisma G, Erdtsieck R, Gerards M, Gerdes V, Haak H, Harbers V, Hoogenberg K, Huvers F, Janssen W, Kars M, Kooy A, Lafeber M, Landewé-Cleuren S, Lieverse A, Meesters E, Moerman S, van Moorsel D, Nijhuis J, Smit CJ, Thevissen K, Timmerman Thijssen DM, Willemsen A, Birkeland K, Cooper J, Gulseth H, Hjelmesæth J, Jørgensen P, Kilhovd BK, Kulseng B, Nicolaisen B, Skadberg Ø, Wium C, Antkowiak-Piatyszek K, Arciszewska M, Bajkowska-Fiedziukiewicz A, Bogdanski P, Czubek U, Cypryk K, Dabrowski J, Dabrowska M, Dziedzic S, Dziewit T, Faligowska M, Fedor-Plenkowska G, Gajos G, Galicka-Latala D, Galuszka-Bilinska A, Gladysz I, Grycewicz J, Hachula G, Janas I, Jazwinska-Tarnawska E, Jedynasty K, Jozefowska M, Kaminska A, Katra B, Kitowska-Koterla J, Klupa T, Koblik T, Konduracka E, Konieczny J, Konieczny M, Kosinski M, Kulkowski G, Kunecki M, Kurmaniak M, Lesniewski R, Lominska T, Losa B, Majkowska D, Malecki M, Mirocka J, Misztal M, Mruk K, Musialik K, Olejniczak H, Opadczuk P, Peczynska J, Plinta M, Polaszewska-Muszynska M, Przech E, Pupek-Musialik D, Ruzga Z, Scibor Z, Sidorowicz-Bialynicka A, Siegel A, Stankiewicz A, Strzelecka-Sosik A, Swierszcz T, Szulinska M, Szymkowiak K, Trybul I, Witek P, Wozniak I, Zambrzycki J, Zarzycka-Lindner G, Zuradzka-Wajda D, Zurawska-Klis M, Ahn HY, Chin SO, Choi SH, Chon S, Han KA, Jang HC, Jeong KC, Kang SM, Kim JW, Kim HS, Kim SJ, Kim SW, Kim YS, Lee EY, Lim S, Min KW, Nam JY, Oh SJ, Park SY, Rhee SY, Shin JA, Son JI, Song YD, Woo JT, Yang HK, Yoo JS, Yoon JW, Avram R, Braicu MD, Carlan L, Catrinoiu D, Ciomos D, Ciorba A, Ghise G, Girgavu S, Guja C, Mihai D, Nicodim S, Nistor L, Pintilei DR, Pintilei E, Pletea N, Pop A, Rosu M, Savu O, Serban V, Sima A, Sitterli-Natea C, Suciu G, Szabo M, Szilagyi I, Timar B, Vlad A, Vladu IM, Alfaraj A, Dubova V, Dvoryashina I, Gaysina L, Gromova S, Gudkova K, Ivanova S, Ivashkina I, Kalashnikova M, Kazankova T, Khaykina E, Khaykina O, Kiseleva T, Komissarova E, Kononenko I, Koreneva V, Koshcheeva O, Koshel L, Kozachuk D, Kufelkina T, Kunitsyna M, Likhodey N, Lysenko T, Makarova O, Malceva A, Mikhailova S, Ogorodnikova E, Pavlikova I, Pekareva E, Postoeva A, Reshedko D, Reshedko G, Reshedko L, Rogaleva A, Rogova L, Rozanov D, Runov G, Samylina I, Semikina T, Sergeeva-Kondrachenko M, Shatskaya O, Shimokhina O, Smetanina S, Startseva M, Strelkova A, Suplotova L, Suvorova L, Sych Y, Valeeva A, Valeeva F, Venjkova T, Vinokurova V, Voychik E, Yanovskaya E, Yanovskaya M, Yarkova N, Yarygina E, Yuzhakova N, Zakharova T, Zanozina O, Zenovko A, Zhuk S, Zhukova E, Aleksic S, Bulatovic A, Buric B, Cvijovic G, Jelic MA, Jojic B, Jotic A, Kendereski A, Lalic K, Lukic L, Macesic M, Petkovic MM, Micic D, Milicic T, Popovic L, Prostran M, Rajkovic N, Seferovic J, Singh S, Stojanovic R, Stosic L, Vuksanovic M, Zamaklar M, Zivkovic TB, Zoric S, Aboo N, Albertse HW, Badat A, Basson M, Bawa E, Bester F, Blignaut S, Booysen S, Bosch FJ, Burgess L, Cassimjee S, Coetzee K, Du Bois J, Engelbrecht J, Finegan K, Gibson GJ, Hansa S, Hemus A, Immink IP, Jacovides A, Joshi P, Joshi S, Kapp C, KhoeleMachobane S, Uys Knox HJ, Kok J, Komati S, Lai E, Lakha D, Lehloenyane K, Mahomed AG, Meeding R, Moodley R, Moosa N, Nel J, Nell H, Van Niekerk FJ, Pillay N, Pretorius M, Prozesky H, Ramduth S, Roos J, Sarvan M, Seeber M, Siebert M, Somasundram P, Stavrides A, Venter N, Wadvalla S, Alcolea JO, Álvarez de Arcaya Vicente A, Pérez Arroyo MB, Romero Bobillo E, Buño MM, Carreira Arias JN, Cepero García D, Masmiquel Comas L, Coves Figueras MJ, de la Cuesta Mayor C, Feria-Carot MD, Frade Fernández AM, Ferreiro Gómez M, García García C, García Delgado E, Durán García S, Gómez Gómez LA, Soto González A, Hernán García C, Ángeles Tapia Herrero M, Jodar Gimeno E, Quevedo Juanals J, López Jiménez M, Masanes F, Marco Mur ÁL, Navarro López M, Ramis JN, Palmer AG, Calle Pascual A, Romero Pérez LG, Morales Portillo C, Prieto González S, Mezquita Raya P, Reyes García R, Vera TR, Rodríguez Castro C, Rodríguez Rodríguez I, Sacanella Meseguer E, Serrano Olmedo I, Lopez Soto A, Toba Alonso F, Aliaga Verdugo A, Vidal Cortada J, Vigil Medina L, Ackefelt-Frick E, Alfredsson H, Beling E, Benedek P, Crisby M, Dorkhan M, Drescik T, Eeg-Olofsson K, Eliasson K, Fardelin P, Fredholm A, Frid A, Gerok-Andersson K, Hjelmaeus L, Hufnagl A, Jasinska E, Kowalska E, Lafolie P, Lindquist O, Lundvall M, Melander E, Nicander C, Moris L, Tengmark BO, Saphir U, Skagerberg P, Steczkó-Nilsson C, Strandell B, Tomson Y, Chen JY, Chen YC, Chiang CY, Chou CW, Ho CW, Hsiao PJ, Hsieh MC, Hsu RS, Hsu SR, Huang CH, Hung WW, Lee MY, Lee YM, Lin CW, Lin CH, Lin KD, Lin SD, Lin SF, Liou MJ, Lu WT, Shin SJ, Sia HK, Su MH, Su SL, Sun JH, Tien KJ, Tsai DH, Tsai SS, Tu ST, Wang CC, Wang SY, Yang CY, Yen FC, Acikgoz A, Akalin S, Akin S, Akinci B, Akkurt A, Akturk M, Alkis N, Altun I, Altunbas HA, Altuntas Y, Araz M, Aribas S, Arslan E, Arslan G, Arslan M, Ataoglu EH, Ayan F, Aydin K, Aydogan BI, Ayvaz G, Bahadir MA, Balci MK, Basaran MN, Baskal N, Bugra MZ, Calan M, Cavdar U, Cetin F, Cinar N, Colbay M, Dagdelen S, Damci T, Davutoglu V, Demir M, Demir T, Deyneli O, Dincer I, Dogan B, Kanipek Doker KY, Engin I, Eraydin A, Erbas T, Erdogan MF, Ersoy C, Gedik A, Gokay F, Gul OO, Guler S, Gumus T, Gunes E, Gurler MY, Hatipoglu E, Ilkova H, Iyidir OT, Kabakci G, Karadag B, Karatemiz G, Karci AC, Kartal E, Kaya EB, Keskin C, Keskin EF, Kocabas G, Kocak F, Kol AK, Korkmaz H, Kucukler FK, Mesci BA, Oguz A, Orbay E, Oz H, Ozcan ND, Ozdem S, Ozisik S, Ozkan C, Ozsan M, Ozyazar M, Parlar H, Sargin H, Sargin M, Saygili F, Selek A, Simsek Y, Sisman P, Solmaz K, Soydas C, Tatliagac S, Tamer I, Temizkan S, Tulunay C, Tuncel E, Turker F, Unluhizarci K, Unluturk U, Uygur MM, Vatansever B, Yazici D, Yavuz DG, Yener S, Yenigun M, Yilmaz M, Abbas S, Alawadi F, Aziz AA, Bashier A, Rashid F, Abraham P, Adamson K, Atkin S, Aye M, Azam M, Barnett AH, Bellary S, Dhatariya K, Eaton M, English P, Ewing J, Furlong N, Gibson M, Green D, Herring R, Hordern V, Jaap A, Javed Z, Johnson A, Konya J, Kumar S, Lindsay R, Mackie A, McGlynn S, McKenzie J, Millward A, Murthy N, Paisey R, Pearson E, Piya M, Ramell M, Robertson D, Russell-Jones D, Saravanan P, Sathyapalan T, Shakher J, Shiels H, Sivaraman S, Smith J, Srinivas-Shankar U, Stokes J, Tracey I, Vaidya B, Yee M, Yemparala P, Walker J, Wiggins P, Williams J, Wright J, Mackinnon C, Inkster J, Zeeshan J, Bejnariu C, Malipatil N, Giritharan S, Lonnen K, Kyrou I, Aamir S, Ababa M, Abreu M, Adams D, Adams P, Aden J, Aguilar D, Aguillon A, Ahmed A, Ahmed B, Ahmed I, Akhtar A, Akright B, Akright L, Albarracin C, Albert S, Ali S, Aliuddin B, Almasmary A, Al-Maweri A, Alzohaili O, Amador W, Amine M, Amini S, Anderson M, Anderson L, Anderson R, Andrews M, Angel J, Anteer W, Anthony V, Antillon A, Anzures P, Arcon-Rios S, Arkin D, Arodak B, Aronne L, Aronoff S, Arreola 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Odugbesan A, Oliver M, Oliver T, Olmeda C, O'Neil C, Oremus R, Ortega T, Ortiz-Santos S, Osborn T, Padmanabhan S, Papacostea O, Park I, Parker A, Parker K, Parker R, Patel C, Patel M, Patel R, Patino M, Patterson S, Paulson K, Paz A, Pemba R, Pepe C, Perez J, Perez T, Perry D, Phillips B, Phillips J, Pickett A, Pinson M, Pitzer R, Poduri M, Poehls J, Poteat T, Powell L, Prasad S, Prevost J, Price E, Priest D, Prieto L, Purewal T, Purighalla R, Purighalla U, Quadrel M, Qureshi A, Radhamma R, Rafla E, Rajab H, Ramalingam R, Ramirez A, Ramirez J, Ramirez K, Ramirez M, Randall M, Rangaraj U, Rao V, Rasmussen P, Rasouli N, Ray A, Reed J, Rems L, Renaud K, Reno M, Resnick M, Reusch J, Reynolds L, Rhoton K, Rhudy J, Ricci C, Rice L, Richardson A, Richardson L, Rickard H, Rickels M, Riff D, Rightenour N, Risser J, Rizvi A, Robertson J, Robinson A, Robinson R, Rockwell M, Rodriguez JP, Rodriguez M, Rojas M, Rojas W, Rooker-Morris L, Root C, Rose M, Rosenberg R, Rosenstock J, Roth M, Ruby R, 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Kennedy, R, Kenney, B, Kereiakes, D, Ketana, M, Kettinger, L, Khaira, A, Khan, A, Khan, K, Khan, M, Khoo, T, Khrlobyan, N, Kilgore, J, Kim, G, Kimble, S, Kinsley, M, Kitchen, T, Klick, M, Kniffen, W, Knight, R, Kodzwa, D, Koenig, T, Komarovskiy, K, Kong, Y, Koontz, D, Krishnasamy, S, Krueger, E, Kuechenmeister, L, Kuehl, A, Kuettel, K, Kugler, D, Kulow, T, Kupriyanchik, I, Kuruvanka, T, Kushner, D, Kwon, E, Kwon, S, Kyle, M, Labryer, L, Labuda, J, Lafave, J, Laguerre, J, Laliberte, A, Lane, J, Langel, C, Lann, D, Largay, J, Latif, K, Latus, T, Lawrence, J, Ledger, G, Lee, Fg, Lee, E, Leffert, J, Leinung, M, Lenhard, Mj, Lentino, J, Leon, J, Leonard, M, Letassy, N, Leuck, K, Levin, P, Levinson, D, Lewis, M, Light, T, Lim, J, Lindamood, R, Lingvay, I, Lipps, J, Lisa, A, Livingston, Y, Llamas, L, Loesch, R, Long, T, Looby, R, Lopez, C, Lorenz, T, Lovre, D, Lu, P, Lucas, K, Luevano, G, Luidens, M, Luna, B, Luttrell, L, Lyons, T, Macadams, M, Mack, D, Mack, M, Madden, M, Madder, R, Madireddy, S, Mae, L, Mahakala, A, Maheshwari, H, Malbari, H, Maldonado, N, Mallitz, M, Mandviwala, M, Mann, K, Mardahay, M, Marino, J, Marney, A, Marshall, L, Martin, A, Martin, E, Martinez, G, Martinez-Miss, S, Marx, P, Massara, L, Mastoor, M, Matfin, G, Maturu, A, Maurides, P, May, M, Mayfield, R, Maynard, B, Mazza, A, Mccann, K, Mccoy, J, Mccoy, T, Mccullen, Mk, Mcdaniel, C, Mcdaniel, Am, Mcdermott, M, Mcdonald, A, Mcmasters, B, Mcmurray, C, Medlin, T, Meinel, M, Mendez, I, Menefee, J, Meredith, M, Merriweather, M, Mersey, J, Messino, C, Meyer, S, Meyers, L, Michael, D, Midyett, C, Miklius, A, Milford, E, Miller, B, Miller, H, Milligan, M, Minor, A, Miranda-Palma, B, Mirarchi, N, Mittadodla, S, Mittle, J, Moffat, A, Mohaupt, S, Mohiuddin, K, Mokshagundam, S, Monaco, S, Monsaert, R, Montano-Pereira, C, Montgomery, A, Moody, K, Moon, M, Moore, D, Moore, L, Morawski, E, Moreau, C, Morin, D, Moscoa, C, Motzkin, C, Mueller, R, Munoz, C, Munoz, M, Myneni, A, Naderi, B, Nagireddy, P, Naidu, J, Naidu, R, Naik, S, Naimark, R, Nardicchi, M, Ndukwu, I, Neller, C, Netten-Foster, L, Neumiller, J, New, T, Newman, S, Newton, T, Nguyen, B, Nicol, B, Nicol, P, Ninivaggi, L, Niswender, K, Norman, L, Noworatzky, G, Nyenwe, E, O'Brien, H, O'Connell, T, Oden, W, Odugbesan, A, Oliver, M, Oliver, T, Olmeda, C, O'Neil, C, Oremus, R, Ortega, T, Ortiz-Santos, S, Osborn, T, Padmanabhan, S, Papacostea, O, Park, I, Parker, A, Parker, K, Parker, R, Patel, C, Patel, M, Patel, R, Patino, M, Patterson, S, Paulson, K, Paz, A, Pemba, R, Pepe, C, Perez, J, Perez, T, Perry, D, Phillips, B, Phillips, J, Pickett, A, Pinson, M, Pitzer, R, Poduri, M, Poehls, J, Poteat, T, Powell, L, Prasad, S, Prevost, J, Price, E, Priest, D, Prieto, L, Purewal, T, Purighalla, R, Purighalla, U, Quadrel, M, Qureshi, A, Radhamma, R, Rafla, E, Rajab, H, Ramalingam, R, Ramirez, A, J, Ramirez, Ramirez, K, Ramirez, M, Randall, M, Rangaraj, U, Rao, V, Rasmussen, P, Rasouli, N, Ray, A, Reed, J, Rems, L, Renaud, K, Reno, M, Resnick, M, Reusch, J, Reynolds, L, Rhoton, K, Rhudy, J, Ricci, C, Rice, L, Richardson, A, Richardson, L, Rickard, H, Rickels, M, Riff, D, Rightenour, N, Risser, J, Rizvi, A, Robertson, J, Robinson, A, Robinson, R, Rockwell, M, Rodriguez, Jp, Rodriguez, M, Rojas, M, Rojas, W, Rooker-Morris, L, Root, C, Rose, M, Rosenberg, R, Rosenstock, J, Roth, M, Ruby, R, Sachson, R, Sack, P, Sadler, Rk, Sahai, S, J, Salazar, Salgam, M, Samal, A, Samson, A, Sanagorski, R, Sanchez, A, Sandberg, J, Sanderson, M, Sandoval, J, Santiago, E, Sapp, T, Saunders, J, Schill, J, Schott, C, Schreiman, R, Schu, D, Schuh, K, Schutta, M, Schwartz, J, Schweppe, L, Scofield, H, Scribner, A, Seal, J, Sealock, J, Seaton, B, Sedlak-Hanslik, T, Seekins, K, Segal, M, Seggelke, S, Semenza, S, Sentman, P, Serra, M, Seshadri, P, Sevilla, E, Shah, S, Shaheen, K, Shanik, M, Shaw, J, Sheets, M, Shellabarger, C, Sher, J, Shippey, J, Shivaswamy, V, Shomali, M, Shore, D, Shroff, P, Siddiqui, T, Siegwald, A, Silver, R, Simmons, D, Simons, R, Sinan, A, Singh, M, Sirinvaravong, S, Skero, J, Slover-Zipf, J, Small, S, Smith, B, Smith, K, Smith, M, Sohl, J, Solarz, Sh, Soler, D, Sood, A, Sora, N, Souchet, A, Soule, J, Sparks, J, Spector, L, Speicher, R, Spillers, L, Spivey, T, Springer, N, Sprouse, H, St John, J, Stacey, A, Stacey, H, Stafford, M, Stagner, E, Staples, K, Steadman, E, Steed, R, Steeves, G, Steinberg, H, Stell, C, Stirman, E, Straub, K, Strock, E, Sue, M, Suris, O, Sutton, T, Tabbah, I, Talsania, M, Tang, R, Tapia, J, Taylor, K, Taylor-Hancher, R, Teator, R, Tekateka, M, Temple, B, Temple, K, Teodori, M, Tharp, P, Thethi, T, Theuma, P, Thomas, S, Thottan, A, Thrasher, J, Thrasher, L, Tiemeyer, M, Tinney, I, Tobin, T, Toma, S, Tovar, M, Townsend, J, Trantow, C, Traylor, H, Trevino, M, Troy, M, Trumper, D, Tryggestad, J, Tucker, C, Turner, J, Turney, R, Tuten, C, Tyzack, J, Ullo, L, Underkofler, C, Unger, J, Urdanetta, R, Valdivia, V, Valenti, S, Vanderheiden, A, Vanderlinde-Wood, M, Varma, C, Vasquez, E, Vazquez, M, Vickery, D, Villafuerte, B, Villegas, C, Vivar, J, Vivekananthan, K, Vo, G, Vukojicic, K, Wachter, A, Wahl, D, Waitmann, J, Walker, D, Walsh, J, Walsh, K, Walton, A, Wang, A, Wardell, K, Watkins, S, Watkinson, J, Watts, M, Watwe, V, Weaver, N, Weber, R, Wedick, C, Weeks, D, Weeks, L, Weindorff, K, Weinstein, R, Weiss, S, Wenger, K, Wentworth, M, Werner, A, West, M, Whelan, S, White, B, White, J, Whitmire, M, Whittington, R, Wical, J, Wigley, C, Wilkins, F, Will, K, Williams, A, Wilson, Le, Wince, M, Wine, S, Winkle, P, Winner, C, Wise, J, Witte, M, Wittenmyer, J, Wood, C, Wood, R, Woodruff, C, Worthington, B, Wynn, D, Wysham, C, Xavier, P, Yela, S, Yenoby, L, Young, L, Younus, N, Yourell, V, Zaid, M, Zubair, I., Mann J.F.E., Orsted D.D., Brown-Frandsen K., Marso S.P., Poulter N.R., Rasmussen S., Tornoe K., Zinman B., Buse J.B., and Buscemi S.

Subjects
Male, Settore MED/09 - Medicina Interna, Acute Kidney Injury, Aged, Albuminuria, Creatinine, Diabetes Mellitus, Type 2, Diabetic Nephropathies, Double-Blind Method, Female, Follow-Up Studies, Glomerular Filtration Rate, Glucagon-Like Peptide 1, Humans, Hypoglycemic Agents, Intention to Treat Analysis, Kidney Failure, Chronic, Liraglutide, Middle Aged, Type 2 diabetes, 030204 cardiovascular system & hematology, urologic and male genital diseases, GLOMERULAR-FILTRATION-RATE, KIDNEY-FUNCTION, DISEASE, law.invention, Kidney Failure, chemistry.chemical_compound, 0302 clinical medicine, Randomized controlled trial, law, Medicine, Settore MED/49 - Scienze Tecniche Dietetiche Applicate, Chronic, RISK, Kidney, Acute kidney injury, 11 Medical And Health Sciences, General Medicine, medicine.anatomical_structure, TRIAL, liraglutide, randomized controlled trial, type 2 diabetes, renal outcomes, Life Sciences & Biomedicine, Type 2, medicine.drug, medicine.medical_specialty, Renal function, 030209 endocrinology & metabolism, CARDIOVASCULAR OUTCOMES, Follow-Up Studie, 03 medical and health sciences, Medicine, General & Internal, General & Internal Medicine, Diabetes mellitus, Internal medicine, Diabetes Mellitus, Intensive care medicine, Science & Technology, business.industry, MORTALITY, medicine.disease, INTENSIVE GLUCOSE CONTROL, INDIVIDUALS, chemistry, Diabetic Nephropathie, LEADER Steering Committee and Investigators, business
Abstract

BACKGROUND: In a randomized, controlled trial that compared liraglutide, a glucagon-like peptide 1 analogue, with placebo in patients with type 2 diabetes and high cardiovascular risk who were receiving usual care, we found that liraglutide resulted in lower risks of the primary end point (nonfatal myocardial infarction, nonfatal stroke, or death from cardiovascular causes) and death. However, the long-term effects of liraglutide on renal outcomes in patients with type 2 diabetes are unknown. METHODS: We report the prespecified secondary renal outcomes of that randomized, controlled trial in which patients were assigned to receive liraglutide or placebo. The secondary renal outcome was a composite of new-onset persistent macroalbuminuria, persistent doubling of the serum creatinine level, end-stage renal disease, or death due to renal disease. The risk of renal outcomes was determined with the use of time-to-event analyses with an intention-to-treat approach. Changes in the estimated glomerular filtration rate and albuminuria were also analyzed. RESULTS: A total of 9340 patients underwent randomization, and the median follow-up of the patients was 3.84 years. The renal outcome occurred in fewer participants in the liraglutide group than in the placebo group (268 of 4668 patients vs. 337 of 4672; hazard ratio, 0.78; 95% confidence interval [CI], 0.67 to 0.92; P=0.003). This result was driven primarily by the new onset of persistent macroalbuminuria, which occurred in fewer participants in the liraglutide group than in the placebo group (161 vs. 215 patients; hazard ratio, 0.74; 95% CI, 0.60 to 0.91; P=0.004). The rates of renal adverse events were similar in the liraglutide group and the placebo group (15.1 events and 16.5 events per 1000 patient-years), including the rate of acute kidney injury (7.1 and 6.2 events per 1000 patient-years, respectively). CONCLUSIONS: This prespecified secondary analysis shows that, when added to usual care, liraglutide resulted in lower rates of the development and progression of diabetic kidney disease than placebo. (Funded by Novo Nordisk and the National Institutes of Health; LEADER ClinicalTrials.gov number, NCT01179048 .).

Published
2017

5. Localized Manifold Harmonics for Spectral Shape Analysis

Author

Melzi, S., Rodolà, E., Castellani, U., Bronstein, M. M., Melzi, S, Rodolà, E, Castellani, U, and Bronstein, M

Subjects
FOS: Computer and information sciences, Spectral geometry processing, Shape analysi, methods and application, 3D shape matching, Mathematics::Spectral Theory, Computational geometry, Methods and applications, Graphics (cs.GR), modelling, Computer Science - Graphics, LBO, signal processing, 3D shape matching, computational geometry, Localization, signal processing, ComputingMethodologies_COMPUTERGRAPHICS
Abstract

The use of Laplacian eigenfunctions is ubiquitous in a wide range of computer graphics and geometry processing applications. In particular, Laplacian eigenbases allow generalizing the classical Fourier analysis to manifolds. A key drawback of such bases is their inherently global nature, as the Laplacian eigenfunctions carry geometric and topological structure of the entire manifold. In this paper, we introduce a new framework for local spectral shape analysis. We show how to efficiently construct localized orthogonal bases by solving an optimization problem that in turn can be posed as the eigendecomposition of a new operator obtained by a modification of the standard Laplacian. We study the theoretical and computational aspects of the proposed framework and showcase our new construction on the classical problems of shape approximation and correspondence. We obtain significant improvement compared to classical Laplacian eigenbases as well as other alternatives for constructing localized bases., Comment: Accepted to Computer Graphics Forum

Published
2017
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6. SHREC'17: Deformable shape retrieval with missing parts

Author

Rodolà, E., Cosmo, L., Litany, O., Bronstein, M., Bronstein, A., Audebert, N., Hamza, A., Castellani, U., Boulch, A., M. N., Do, Duong, A. -D., Furuya, T., Gasparetto, A., Hong, Y., Kim, J., Le Saux, B., Litman, R., Masoumi, M., Minello, G., Nguyen, H. -D., Nguyen, V. -T., Ohbuchi, R., Pham, V. -K., Phan, T. V., Rezaei, M., Torsello, A., Tran, M. -T., Tran, Q. -T., Truong, B., Wan, L., and Zou, C.

Subjects
Shape Analysis, Deformable Shape, Settore INF/01 - Informatica, Retrieval algorithms, 3D shape retrieval, 3D shape retrieval, Shape Analysis, Geometry processing, Geometry processing, Missing parts
Published
2017

7. Learning shape correspondence with anisotropic convolutional neural networks

Author

Boscaini, D., Masci, J., Emanuele Rodolà, and Bronstein, M.

Subjects
FOS: Computer and information sciences, Benchmarking, Computer graphics, Anisotropy, Computer Vision and Pattern Recognition (cs.CV), ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Computer Science - Computer Vision and Pattern Recognition, ComputingMethodologies_COMPUTERGRAPHICS
Abstract

Establishing correspondence between shapes is a fundamental problem in geometry processing, arising in a wide variety of applications. The problem is especially difficult in the setting of non-isometric deformations, as well as in the presence of topological noise and missing parts, mainly due to the limited capability to model such deformations axiomatically. Several recent works showed that invariance to complex shape transformations can be learned from examples. In this paper, we introduce an intrinsic convolutional neural network architecture based on anisotropic diffusion kernels, which we term Anisotropic Convolutional Neural Network (ACNN). In our construction, we generalize convolutions to non-Euclidean domains by constructing a set of oriented anisotropic diffusion kernels, creating in this way a local intrinsic polar representation of the data (`patch'), which is then correlated with a filter. Several cascades of such filters, linear, and non-linear operators are stacked to form a deep neural network whose parameters are learned by minimizing a task-specific cost. We use ACNNs to effectively learn intrinsic dense correspondences between deformable shapes in very challenging settings, achieving state-of-the-art results on some of the most difficult recent correspondence benchmarks.

Published
2016

10. SHREC'16: Partial matching of deformable shapes

Author

Cosmo, L., Rodolà, E., Bronstein, M. M., Torsello, A., Cremers, D., and Sahillioǧlu, Y.

Subjects
Settore INF/01 - Informatica, 3D shapes, Matching algorithms, Deformable shapes
Published
2016

11. A study of the dynamic effects on the design loads of a civil aircraft

Author

Bronstein, M, Feldman, E, Vescovini, R, and Bisagni, C.

Abstract

The daedalos project was supported by the european commission under the programme transport (including aeronautics) of the 7th framework programme for research and technological development, grant agreement no: 266411. Daedalos stands for dynamics in aircraft engineering design and analysis for light optimized structures The primary objective of the daedalos project is to investigate the dynamic effects on the actual loads acting on the airframe for improved definition of the sizing loads for structural components of civil aircrafts.

Published
2016

12. Partial Functional Correspondence

Author

Rodolà, E., Cosmo, L., Bronstein, M. M., Torsello, A., and Cremers, D.

Subjects
FOS: Computer and information sciences, Functional maps, Partial similarity, Shape matching, Computer Networks and Communications, Settore INF/01 - Informatica, functional maps, i.3.5 [computational graphics], computational geometry and object modelling-shape analysis, partial similarity, shape matching, computer networks and communications, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition
Abstract

In this paper, we propose a method for computing partial functional correspondence between non-rigid shapes. We use perturbation analysis to show how removal of shape parts changes the Laplace-Beltrami eigenfunctions, and exploit it as a prior on the spectral representation of the correspondence. Corresponding parts are optimization variables in our problem and are used to weight the functional correspondence; we are looking for the largest and most regular (in the Mumford-Shah sense) parts that minimize correspondence distortion. We show that our approach can cope with very challenging correspondence settings.

Published
2015

13. Die kernspintomographische Diagnostik der Appendizitis bei Kindern und Jugendlichen – eine Metaanalyse

Author

Muensterer, O, Bronstein, M, and Pandya, S

Subjects
ddc: 610, 610 Medical sciences, Medicine
Abstract

Einleitung: Die Appendizitis ist der häufigste chirurgische Notfall im Kindes- und Jungendalter. Die Ultraschalldiagnostik weist bei guter Spezifität leider eine niedrige Sensitivität auf. Daher wird bei unklaren Fällen vor allen in den USA häufig ein Computertomogram durchgeführt,[for full text, please go to the a.m. URL], 132. Kongress der Deutschen Gesellschaft für Chirurgie

Published
2015
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15. SHREC'14 Track: Shape retrieval of non-rigid 3D human models

Author

Pickup, David, Martin, Ralph Robert, Rosin, Paul L., Sun, Xianfang, Cheng, Z., Lian, Z., Aono, M., Ben Hamza, A., Bronstein, A., Bronstein, M., Bu, S., Castellani, U., Cheng, S., Garro, V., Giachetti, A., Godil, A., Han., J., Johan, H., Lai, L., Li, B., Li, C., Li, H., Litman, R., Liu, X., Liu, Z., Lu, Y, Tatsuma, A., and Ye, J.

Abstract

We have created a new benchmarking dataset for testing non-rigid 3D shape retrieval algorithms, one that is much more challenging than existing datasets. Our dataset features exclusively human models, in a variety of body shapes and poses. 3D models of humans are commonly used within computer graphics and vision, and so the ability to distinguish between body shapes is an important shape retrieval problem. In this track nine groups have submitted the results of a total of 22 different methods which have been tested on our new dataset.

Published
2014

16. Estudio comparativo sobre reconstrucción post-endodoncia en grupos de pacientes de la ciudad de Córdoba

Author

Arena, AL., Moreno, M., Gioino, G., Gómez, C., Luján, G., Carvajal, M., Garofletti, J., Bronstein, M., and Crohare, L.

Subjects
ESTUDIO, COMPARATIVO, RECONSTRUCCIÓN, POST-ENDODONCIA
Abstract

Coautor. Trabajo: Estudio comparativo sobre reconstrucción post-endodoncia en grupos de pacientes de la ciudad de Córdoba. Boletín Informativo, Sociedad Argentina de Endodoncia, Nº 44, Septiembre de 2013. Página 10 publishedVersion Odontología, Medicina y Cirugía Oral

Published
2013

17. Disección mucosal endoscópica de cáncer gástrico en paciente con poliposis colonica

Author

Cumana, R, Bronstein, M, Salazar, J, Soto, J, Fuentes, D, Isern, A, Fernández, C, Soto, M, and Maradey, C

Subjects
Disección, Early, Polyps, Precoz, Dissection, Polipos
Abstract

La disección mucosal endoscópica (DME), surge a partir de la resección mucosal endoscópica (RME), permitiendo resecar lesiones malignas en estadio precoz, logrando tasas de curación de hasta el 99%, disminuyendo la morbi-mortalidad de la cirugía tradicional. Es importante la obtención de la pieza de forma completa, ya que de esta manera, el patólogo podrá informar los márgenes de la lesión en extensión y profundidad. Caso clínico: Se trata de paciente masculino de 40 años de edad, valorado por nuestro servicio (agosto 2009) por clínica de 4 meses de evolución, dado por cambios en el patrón evacuatorio (evacuaciones diarreicas) y rectorragia. Consulta a especialista, el cual realiza colonoscopia con hallazgo de tumor en recto medio, con biopsia positiva para Adenocarcinoma, por lo que refieren a nuestro centro. Antecedentes personales y familiares: no contributorios. Se realizó gastroscopia la cual reporta: Lesión en cara anterior de antro, elevada, fondo ulcerado, deprimido, amputación de pliegues; se concluye: Ca. Gástrico Precoz IIc. Ultrasonido Endoscópico: Engrosamiento de la mucosa y muscular de la mucosa en antro. Cara posterior. Biopsia: Sin atipias. Colonoscopia: Tu recto bajo. Poliposis colonica. Ultrasonido endoscópico transrectal: Tu. Recto bajo uT2N1. Biopsia: Adenocarcinoma Moderadamente diferenciado. En vista de las características de la lesión gástrica, se decide realizar disección mucosal endoscópica, cuya biopsia que reporta: Carcinoma intramucoso precoz, bordes de resección libres de lesión. Paciente recibe tratamiento oncológico neo-adyuvante y posteriormente se realiza ileoprocto anastomosis. Evolución actual satisfactoria. Discusión: La apariencia endoscópica de las lesiones juega un papel importante en la conducta a seguir por el médico y es clave al momento de plantearse la realización de DME, ya que es un procedimiento que conlleva riesgos y tiene indicaciones especificas, para obtener así los resultados planteados. Ha demostrado ser un método seguro y eficaz en el tratamiento del cáncer precoz, no solo de estómago sino esófago y colon, aumentando la sobrevida del paciente. Los pacientes con poliposis colonica sin antecedentes familiares suelen presentar los síntomas a edad más precoz y la tendencia a padecer carcinoma colonico es mayor. La edad promedio de aparición de los pólipos oscila de 26 a 28 años y el intervalo entre la aparición de los adenomas y los síntomas es de 10 años. Cabe destacar que estos pacientes pueden presentar manifestaciones extra-intestinales, y la aparición de cáncer en otras localizaciones del tracto digestivo; un 10% de estos están relacionados el cáncer gástrico. Es importante la pesquisa mediante realización de endoscopias en este tipo de pacientes. Endoscopic mucosal dissection (DME), arises from endoscopic mucosal resection (EMR), allowing resection malignant lesions in early stage, achieving cure rates of up to 99%, decreasing morbidity and mortality of traditional surgery. It is important to obtain the piece completely, as this way, the pathologist may report the margins of the lesion extent and depth. Case report: This male patient aged 40 years, valued for our service (August 2009) by clinical evolution of 4 months, changes in the pattern of voiding (bowel diarrhea) and bleeding rectal. Consulting specialist, performed colonoscopy finding means is rectal tumor, with positive biopsy for adenocarcinoma, so refer to our center. Personal and family history: no contributory. Gastroscopy was performed which reported: Injury anterior antrum, high background ulcerated, depressed, amputation of folds, it is concluded: IIc early gastric Ca. Endoscopic Ultrasound: Thickening of the mucosa and muscle of the antral mucosa. Posterior. Biopsy: No atypia. Colonoscopy: tu. lower rectum. Colonic polyposis. Transrectal endoscopic ultrasound: Tu. UT2N1 lower rectum. Biopsy: moderately differentiated adenocarcinoma. Given the characteristics of gastric injury is endoscopic submucosal dissection dedide perform, with biopsy reports: early intramucosal carcinoma, resection margins free of injury. patient receives Neoadjuvant cancer treatment and subsequently coloproctoanastomosis. Current developments satisfactory. Discussion: The endoscopic appearance of lesions plays an important role in the conduct to be followed by the doctor and is key to consider when conducting DME because it is a procedure that carries risks and has specific indications for and results obertener raised. It has proven to be safe and effective in the treatment of early cancer, but not only esophageal stomach and colon, increasing patient survival. Colonic polyposis patients without family history often have symptoms at younger age and prone to colonic carcinoma is higher. The average age of onset of polyps ranged from 26 to 28 years and the interval between the onset of adenomas and symptoms is 10 years. Importantly, these patients may have extraintestinal manifestations, and cancer in other locations in the digestive tract, 10% of these are related to the occurrence of gastric cancer. It is important to the investigation by endoscopy in these patients.

Published
2011

19. Hemobilia: diagnóstico por imágenes. A propósito de dos casos

Author

Cumana, R, Fernández, C, Isern, A, Bronstein, M, Senior, M, Soto, J, Salazar, J, Fuentes, D, Gumina, C, Mago, V, Soto, M, and Maradey, C

Subjects
Hemobilia, Ultrasonido, Ultrasound, Aneurismas, Aneurysm
Abstract

El diagnóstico de hemobilia resulta difícil en la práctica diaria; el tratamiento está destinado a detener el sangrado y resolver la causa del mismo. Los aneurismas de la arteria hepática constituyen una patología poco frecuente y una de las causas raras de hemobilia, la presentación clínica es inespecífica e incluye dolor abdominal, ictericia obstructiva y sangrado digestivo alto. Recientemente con el desarrollo de la radiología intervencionista se ha logrado reducir el número de cirugías, mediante la embolización transarterial, obteniendo tasas de éxito entre 80-100%.² Se presentaran 2 casos de hemobilia, todos fueron estudiados con ecografía, colangiografía por resonancia magnética y angiotomografía. Se describen las características de esta patología con los distintos métodos por imágenes; se destaca la indicación de la arteriografía no sólo para el diagnóstico sino también como tratamiento (embolización). En un caso, la hemobilia fue identificada por duodenoscopia y en el otro por gastroscopia. A ambos pacientes se le realizó ultrasonido abdominal el cual mostró hepatomegalia, vesícula distendida con barro biliar, dilatación de vías biliares e imagen hipoecogénica en segmento V hepático. El doppler revela flujo activo en la vía biliar. Angiotomografía y colangiografía por resonancia magnetica revelaron aneurisma en la arteria hepática derecha en íntimo contacto con la vía biliar, correlacionado con la imágen hipoecogénica observada por ultrasonido. Ambos casos fueron resueltos por la liberación de coils intra-arteriales sin complicaciones. The diagnosis of hemobilia is difficult in daily practice; treatment is designed to stop the bleeding and resolve its cause. Hepatic artery aneurysms are an uncommon condition and one of the rare causes of hemobilia; clinical presentation is nonspecific and includes abdominal pain, obstructive jaundice and upper gastrointestinal bleeding. Recently, due to the development of interventional radiology, the number of surgeries has successfully been reduced through transarterial embolization, achieving success rates between 80-100%.² We present 2 cases of hemobilia that were evaluated by ultrasound, MRI cholangiography and angiotomography. We describe the characteristics of this disease with the use of different imaging methods; with emphasis on the use of arteriography not only for diagnosis but also for treatment (embolization). In one case, the hemobilia was identified by duodenoscopy, and in the other by gastroscopy. Both patients underwent abdominal ultrasound that showed hepatomegaly, distended gallbladder with biliary sludge, distended bile ducts and a hypoechoic image in liver segment V. Doppler revealed active flow into the bile duct. Angiotomography and MRI reported an aneurysm in the right hepatic artery in close contact to the bile duct, correlated to the hypoechoic image seen by ultrasound. Both cases were treated with transarterial coil placements without any complications.

Published
2011

20. GWA study data mining and independent replication identify cardiomyopathy-associated 5 (CMYA5) as a risk gene for schizophrenia

Author

Blackman, J, Lee, G, Shi, J, Craddock, N J, van den Oord, E, Zhao, Z, Owen, M J, Schwab, S, Levinson, D F, Walsh, D, Sullivan, P F, Duan, J, O'Donovan, M C, O'Neill, F A, Lencz, T, Gejman, P V, Chen, X, Nimgaonkar, V, Chowdari, K, Darvasi, A, Bronstein, M, Kirov, G K, Sanders, A, Lewis, D, Weinberger, D R, Guo, A, Chen, J, Maher, B S, Qin, W, Wildenauer, D, Fanous, A H, and Straub, R E

Abstract

We conducted data-mining analyses using the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) and molecular genetics of schizophrenia genome-wide association study supported by the genetic association information network (MGS-GAIN) schizophrenia data sets and performed bioinformatic prioritization for all the markers with P-values ≤0.05 in both data sets. In this process, we found that in the CMYA5 gene, there were two non-synonymous markers, rs3828611 and rs10043986, showing nominal significance in both the CATIE and MGS-GAIN samples. In a combined analysis of both the CATIE and MGS-GAIN samples, rs4704591 was identified as the most significant marker in the gene. Linkage disequilibrium analyses indicated that these markers were in low LD (3 828 611–rs10043986, r2 = 0.008; rs10043986–rs4704591, r2 = 0.204). In addition, CMYA5 was reported to be physically interacting with the DTNBP1 gene, a promising candidate for schizophrenia, suggesting that CMYA5 may be involved in the same biological pathway and process. On the basis of this information, we performed replication studies for these three single-nucleotide polymorphisms. The rs3828611 was found to have conflicting results in our Irish samples and was dropped out without further investigation. The other two markers were verified in 23 other independent data sets. In a meta-analysis of all 23 replication samples (family samples, 912 families with 4160 subjects; case–control samples, 11 380 cases and 15 021 controls), we found that both markers are significantly associated with schizophrenia (rs10043986, odds ratio (OR) = 1.11, 95% confidence interval (CI) = 1.04–1.18, P = 8.2 × 10−4 and rs4704591, OR = 1.07, 95% CI = 1.03–1.11, P = 3.0 × 10−4). The results were also significant for the 22 Caucasian replication samples (rs10043986, OR = 1.11, 95% CI = 1.03–1.17, P = 0.0026 and rs4704591, OR = 1.07, 95% CI = 1.02–1.11, P = 0.0015). Furthermore, haplotype conditioned analyses indicated that the association signals observed at these two markers are independent. On the basis of these results, we concluded that CMYA5 is associated with schizophrenia and further investigation of the gene is warranted.

Published
2011
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21. Tumores sólido pseudopapilares del pancreas: Presentación de 2 casos

Author

Maradey, C, Cumana, R, Soto, M, Graterol, A, Isern, A, Fernandez, C, Bronstein, M, Fuentes, D, Salazar, J, Senior, M, and Soto, J

Subjects
Pancreatoduodenectomía, Pancreatectomía distal, Páncreas, pancreatoduodenectomy, Neoplasias quísticas del páncreas, Solid pseudopapillary tumor, Distal pancreatectomy, Tumor sólido pseudopapilar, Cystic neoplasms of the pancreas, Pancreas
Abstract

Las neoplasias quísticas del páncreas representan menos del 10 % de las neoplasias pancreáticas, comprendiendo una gama de lesiones benignas, limítrofes y malignas, según la OMS. Dentro de estos tumores reviste importancia el Tumor sólido pseudopapilar, a pesar de su baja incidencia a nivel mundial, entre 1-2% de las neoplasias pancreáticas, y ser considerado como de bajo potencial maligno, es decir limítrofe. Sin embargo, son tumores invasivos, con la capacidad de diseminarse localmente o a distancia hasta en un 15 % aproximadamente. Se ha descrito la resección quirúrgica radical como tratamiento de elección para esta patología; pancreatoduodenectomía para los tumores localizados en la cabeza del páncreas, y pancreatectomía distal combinada o no con esplenectomía, para los ubicados en cuerpo y cola. A propósito de esta infrecuente neoplasia quística del páncreas, reportamos dos (2) casos evaluados y tratados por el Departamento de Vías digestivas del Servicio Oncológico Hospitalario del IVSS, durante el año en curso, con resultados satisfactorios. Cystic neoplasms of the pancreas represent less than 10% of pancreatic tumors, comprising a range of benign, borderline and malignant, according to WHO. Within these tumors is important solid pseudopapillary tumor, despite its low incidence worldwide (1-2% of cystic neoplasms of the pancreas), and be considered of low malignant potential, considered borderline. However, despite these features, are invasive tumors, with the ability to spread locally or remotely up to 15%. It has been described radical surgical resection as treatment of choice for this disease; pancreatoduodenectomy for pancreatic head tumor and Distal pancreatectomy with or without splenectomy, for pancreatic body and/or tail tumor. About this rare cystic neoplasm of the pancreas, we report two (2) cases evaluated and treated by the Digestive tract disease department at the Oncology Hospital Service of IVSS, during this year, with satisfactory results.

Published
2011

22. Ultrasonido endoscópico y puncion aspiración con aguja fina en tumores del páncreas: experiencia de 2 años

Author

Isern, A.M, Fernández, C, Graterol, A, Figueira, C, Ruiz, C, Essenfeld, H, Fuentes, D, Bronstein, M, Soto, J, Salazar, J, Cumana, R, Maradey, C, and Soto, M

Subjects
pancreatic neoplasm, Ultrasonido endoscópico, Endoscopic ultrasound, tumores de páncreas
Abstract

La punción aspiración guiada por ultrasonido endoscópico (PAAF-USE) se ha convertido en una herramienta fundamental en el diagnóstico de los tumores de páncreas. Es un procedimiento con baja tasa de complicaciones que además provee información determinante que puede modificar la conducta terapéutica. Métodos: Estudio retrospectivo, descriptivo. Se incluyeron pacientes con diagnóstico de tumor de páncreas referidos para la realización PAAF-USE en el período comprendido entre 2008-2009. Resultados: 36 pacientes fueron estudiados, 58.30% (n=21) del sexo femenino. Se evidenciaron tumores sólidos en el 80.5%. Según la histología, fueron reportados adenocarcinoma en el 47.05% (n=16), cistoadenoma mucinoso en el 8.88% (n=3), cistoadenocarcinoma en el 5.88% (n=2), linfoma no Hodgkin en el 5.88% (n=2), tumor neuroendocrino (insulinoma) en el 2.94 % (n=1), cistodenoma seroso en el 2.94% (n=1), tumor sólido pseudopapilar en el 2.94% (n=1), tumor metastásico a páncreas en el 2.94% (n=1) y el 17.64% (n=6) fueron reportados negativos para malignidad. No hubo complicaciones asociadas al procedimiento. Conclusiones: Los hallazgos obtenidos por PAAF-USE permiten establecer el diagnóstico en un alto porcentaje de las lesiones tumorales del páncreas, con una baja tasa de complicaciones, permitiendo seleccionar conductas terapéuticas adecuadas. Endoscopic ultrasound-guided fine-needle-aspiration (EUS-FNA) has become an essential tool for the diagnosis and staging of pancreatic neoplasms. It is a procedure with low complication rates and also provides crucial information which could alter the therapeutic management. Methods: A retrospective analysis of patients referred for USE-FNA with presumed pancreatic neoplasms between January 2008 and December 2009. Results: 36 patients were studied, 58.30% (n = 21) were females. Solid tumors were evident in 80.5%. According to their histology, adenocarcinoma were reported in 47.05% (n = 16), mucinous cystadenoma in 8.88% (n = 3), cystadenocarcinoma in 5.88% (n = 2), non-Hodgkin lymphoma in 5.88% (n = 2), neuroendocrine tumor (insulinoma) in 2.94% (n = 1), serous cystoadenoma in 2.94% (n = 1), solid pseudopapillary tumor in 2.94% (n = 1), metastatic tumor 2.94 % (n = 1) and 17.64% (n = 6) were reported negative for malignancy. There were no complications associated with the procedure. Conclusions: The findings obtained by EUS-FNA make diagnosis possible in a high percentage of tumoral lesions of the pancreas, with no procedural complication rates overall in this study. Consequently, the accurate histological diagnosis will have the potential to affect the selection of an appropriate treatment.

Published
2011

23. SHREC 2010: robust correspondence benchmark

Author

Bronstein, A. M., Bronstein, M. M., Castellani, Umberto, Dubrovina, A., Guibas, L. J., Horaud, R. P., Kimmel, R., Knossow, D., von Lavante, E., Mateus, D., and Ovsjanikov, M.

Subjects
3D object retrieval, shape descriptors, shape matching
Published
2010

25. SHREC 2010: robust feature detection and description benchmark

Author

Bronstein, A. M., Bronstein, M. M., Bustos, B., Castellani, Umberto, Cristani, Marco, Falcidieno, B., Guibas, L. J., Kokkinos, I., Murino, Vittorio, Ovsjanikov, M., Patané, G., Sipiran, I., Spagnuolo, M., and Sun, J.

Subjects
3D object retrieval, shape descriptors, shape matching
Published
2010

26. Criteria for the definition of Pituitary Tumor Centers of Excellence (PTCOE): A Pituitary Society Statement

Author

Casanueva, FF, Barkan, AL, Buchfelder, M, Klibanski, A, Laws, ER, Loeffler, JS, Melmed, S, Mortini, P, Wass, J, Giustina, A, Lomba, AA, Abucham, J, Alvarez-Escola, C, Beckers, A, Ben-Shlomo, A, Bernabeu, I, Bidlingmaier, M, Biermasz, N, Biller, B, Boguszewski, CL, Bolanowski, M, Bollerslev, J, Bonert, V, Bronstein, M, Bruno, OD, Carmichael, JD, Caron, P, Chanson, P, Clayton, RN, Colao, A, Cordido, F, De Marinis, L, Fahlbusch, R, Fleseriu, M, Formenti, AM, Freda, PU, Fukuoka, H, Ghigo, E, Greenman, Y, Grineva, E, Grossman, A, Gurnell, M, Heaney, A, Hoffman, AR, Ilovayskaya, I, Johannsson, G, Kadioglu, P, Karavitaki, N, Katznelson, L, Kelestimur, F, Kelly, DF, Ho, K, Krsek, M, Lacroix, A, StevenLoeffler, J, Losa, M, Jørgensen, JO, Luger, A, Mallea-Gil, S, Mamelak, A, Mazziotti, G, McCormack, A, Mercado, M, Neggers, S, Ning, G, Oyesiku, NM, Popovic, V, Petakov, M, Petersenn, S, Pfeifer, M, Pico, A, Domingo, MP, Raverot, G, Reincke, M, Gadelha, MR, Salvatori, R, Samson, SL, Shimatsu, A, Shimon, I, Stewart, P, Strasburger, C, Swearingen, B, Trainer, P, Tritos, NA, Tsagarakis, S, Van Der Lely, AJ, Vilar, L, Villar-Taibo, R, and Zatelli, MC

Subjects
Male, Thyrotropinomas, Pituitary Diseases, Cushing’s disease, United States, 3. Good health, Pituitary radiotherapy, Treatment Outcome, Transsphenoidal surgery, Pituitary Gland, Acromegaly, Humans, Female, Pituitary Neoplasms, Pituitary ACTH Hypersecretion, Gonadotropins, Societies, Medical
Abstract

Introduction With the goal of generate uniform criteria among centers dealing with pituitary tumors and to enhance patient care, the Pituitary Society decided to generate criteria for developing Pituitary Tumors Centers of Excellence (PTCOE). Methods To develop that task, a group of ten experts served as a Task Force and through two years of iterative work an initial draft was elaborated. This draft was discussed, modified and finally approved by the Board of Directors of the Pituitary Society. Such document was presented and debated at a specific session of the Congress of the Pituitary Society, Orlando 2017, and suggestions were incorporated. Finally the document was distributed to a large group of global experts that introduced further modifications with final endorsement. Results After five years of iterative work a document with the ideal criteria for a PTCOE is presented. Conclusions Acknowledging that very few centers in the world, if any, likely fulfill the requirements here presented, the document may be a tool to guide improvements of care delivery to patients with pituitary disorders. All these criteria must be accommodated to the regulations and organization of Health of a given country.

28. Partition and Code: learning how to compress graphs

Author

Giorgos Bouritsas, Loukas, A., Karalias, N., and Bronstein, M. M.

Subjects
Social and Information Networks (cs.SI), FOS: Computer and information sciences, Computer Science - Machine Learning, Statistics - Machine Learning, Information Theory (cs.IT), Computer Science - Information Theory, Machine Learning (stat.ML), Computer Science - Social and Information Networks, Data_CODINGANDINFORMATIONTHEORY, Machine Learning (cs.LG)
Abstract

Can we use machine learning to compress graph data? The absence of ordering in graphs poses a significant challenge to conventional compression algorithms, limiting their attainable gains as well as their ability to discover relevant patterns. On the other hand, most graph compression approaches rely on domain-dependent handcrafted representations and cannot adapt to different underlying graph distributions. This work aims to establish the necessary principles a lossless graph compression method should follow to approach the entropy storage lower bound. Instead of making rigid assumptions about the graph distribution, we formulate the compressor as a probabilistic model that can be learned from data and generalise to unseen instances. Our "Partition and Code" framework entails three steps: first, a partitioning algorithm decomposes the graph into subgraphs, then these are mapped to the elements of a small dictionary on which we learn a probability distribution, and finally, an entropy encoder translates the representation into bits. All the components (partitioning, dictionary and distribution) are parametric and can be trained with gradient descent. We theoretically compare the compression quality of several graph encodings and prove, under mild conditions, that PnC achieves compression gains that grow either linearly or quadratically with the number of vertices. Empirically, PnC yields significant compression improvements on diverse real-world networks., Published at NeurIPS 2021

33. Learning invariant representations in neural networks

Author

Fuchs, FB, Kumar, P, Bronstein, M, and Posner, H

Subjects
Machine learning
Abstract

Symmetries and invariances are ubiquitous in machine learning tasks. While convolutional neural networks famously and successfully exploit translational symmetries, other symmetries have, until recently, often been neglected. Incorporating symmetries or invariances into the neural network architecture avoids costly data augmentation and alleviates the need for large datasets. The presented work focuses on invariant and equivariant neural network layers, putting symmetries at the centre of neural network architecture design. Concretely, this thesis covers three different invariances: permutation invariance, roto-translation invariance, and label invariance. • For permutation invariance, this work presents an analysis of the capacity and constraints of sum aggregation, one of the most used permutation invariant neural network paradigms. Next, different permutation invariant relational reasoning modules in the context of multi-object tracking are proposed and compared. • For roto-translation invariance, a new roto-translation equivariant graph network based on self-attention is introduced. In a subsequent step, this is adapted to enable iterative position refinement, a crucial feature for protein structure prediction. • Lastly, the case is covered where there is no known symmetry group but instead a nuisance factor that the practitioner would like the neural network to be invariant to. We refer to this concept as label invariance. To that end, a neural network module is introduced that can promote or suppress the nuisance factor while simultaneously making the network more interpretable.

Published
2022

34. Consensus on Diagnosis and Management of Cushing’s Disease: A Guideline Update

Author

Stylianos Tsagarakis, Ashley B. Grossman, André Lacroix, Maria Chiara Zatelli, Hershel Raff, Lynnette K. Nieman, Eliza B Geer, Cesar Luiz Boguszewski, Beverly M. K. Biller, Marily Theodoropoulou, Mark E. Molitch, Daniel F. Kelly, Alberto M. Pereira, Marcello D. Bronstein, Brooke Swearingen, Stephan Petersenn, Irina Bancos, Adriana G. Ioachimescu, Frederic Castinetti, Ken K. Y. Ho, Ilan Shimon, Martin Reincke, Susan M. Webb, Richard J. Auchus, John Newell-Price, Roberto Salvatori, Shlomo Melmed, Carla Scaroni, Maria Fleseriu, Ursula B. Kaiser, Greisa Vila, Jérôme Bertherat, Anat Ben-Shlomo, Andrea Giustina, Mônica R. Gadelha, Michael Buchfelder, James W. Findling, Mark Gurnell, Rosario Pivonello, Philippe Chanson, Yutaka Takahashi, John A.H. Wass, Nienke R. Biermasz, Ann McCormack, Niki Karavitaki, Felipe F. Casanueva, Laurence Katznelson, Elena Valassi, Antoine Tabarin, John D. Carmichael, Pietro Mortini, Constantine A. Stratakis, Elena V. Varlamov, Fleseriu, M., Auchus, R., Bancos, I., Ben-Shlomo, A., Bertherat, J., Biermasz, N. R., Boguszewski, C. L., Bronstein, M. D., Buchfelder, M., Carmichael, J. D., Casanueva, F. F., Castinetti, F., Chanson, P., Findling, J., Gadelha, M., Geer, E. B., Giustina, A., Grossman, A., Gurnell, M., Ho, K., Ioachimescu, A. G., Kaiser, U. B., Karavitaki, N., Katznelson, L., Kelly, D. F., Lacroix, A., Mccormack, A., Melmed, S., Molitch, M., Mortini, P., Newell-Price, J., Nieman, L., Pereira, A. M., Petersenn, S., Pivonello, R., Raff, H., Reincke, M., Salvatori, R., Scaroni, C., Shimon, I., Stratakis, C. A., Swearingen, B., Tabarin, A., Takahashi, Y., Theodoropoulou, M., Tsagarakis, S., Valassi, E., Varlamov, E. V., Vila, G., Wass, J., Webb, S. M., Zatelli, M. C., and Biller, B. M. K.

Subjects
medicine.medical_specialty, business.industry, Endocrinology, Diabetes and Metabolism, Medizin, Treatment options, Guideline, Disease, Cushing's disease, medicine.disease, Article, NO, Clinical Practice, Endocrinology, Pituitary, cushing disease, Internal Medicine, Medicine, Medical physics, LS4_3, business
Abstract

Summary Cushing's disease requires accurate diagnosis, careful treatment selection, and long-term management to optimise patient outcomes. The Pituitary Society convened a consensus workshop comprising more than 50 academic researchers and clinical experts to discuss the application of recent evidence to clinical practice. In advance of the virtual meeting, data from 2015 to present about screening and diagnosis; surgery, medical, and radiation therapy; and disease-related and treatment-related complications of Cushing's disease summarised in recorded lectures were reviewed by all participants. During the meeting, concise summaries of the recorded lectures were presented, followed by small group breakout discussions. Consensus opinions from each group were collated into a draft document, which was reviewed and approved by all participants. Recommendations regarding use of laboratory tests, imaging, and treatment options are presented, along with algorithms for diagnosis of Cushing's syndrome and management of Cushing's disease. Topics considered most important to address in future research are also identified.

Published
2021

35. Multidisciplinary management of acromegaly: a consensus

Author

Nienke R. Biermasz, Mark E. Molitch, Jens Bollerslev, Kevin C J Yuen, Anat Ben-Shlomo, Adam N. Mamelak, Marcello D. Bronstein, Ilan Shimon, Manuel Puig-Domingo, Eliza B Geer, Anna Maria Formenti, Margaret E. Wierman, Pietro Maffei, Mônica R. Gadelha, Pamela U. Freda, Marek Bolanowski, David R. Clemmons, Adriana G. Ioachimescu, Edward R. Laws, Michael Buchfelder, John A.H. Wass, Steven W. J. Lamberts, Brooke Swearingen, Kalmon D. Post, Maria Chiara Zatelli, Felipe F. Casanueva, Vivien Bonert, Anthony P. Heaney, Philippe Chanson, Christian J. Strasburger, Susan L. Samson, Pietro Mortini, Cesar Luiz Boguszewski, Beverly M. K. Biller, Garni Barkhoudarian, Roberto Salvatori, Albert Beckers, Marco Losa, Alberto M. Pereira, Shlomo Melmed, Andrea Giustina, Maria Fleseriu, Mark Gurnell, Mary Lee Vance, Stephan Petersenn, Ken K. Y. Ho, Peter J Trainer, Moisés Mercado, Giustina, A., Barkhoudarian, G., Beckers, A., Ben-Shlomo, A., Biermasz, N., Biller, B., Boguszewski, C., Bolanowski, M., Bollerslev, J., Bonert, V., Bronstein, M. D., Buchfelder, M., Casanueva, F., Chanson, P., Clemmons, D., Fleseriu, M., Formenti, A. M., Freda, P., Gadelha, M., Geer, E., Gurnell, M., Heaney, A. P., Ho, K. K. Y., Ioachimescu, A. G., Lamberts, S., Laws, E., Losa, M., Maffei, P., Mamelak, A., Mercado, M., Molitch, M., Mortini, P., Pereira, A. M., Petersenn, S., Post, K., Puig-Domingo, M., Salvatori, R., Samson, S. L., Shimon, I., Strasburger, C., Swearingen, B., Trainer, P., Vance, M. L., Wass, J., Wierman, M. E., Yuen, K. C. J., Zatelli, M. C., Melmed, S., Gurnell, Mark [0000-0001-5745-6832], Apollo - University of Cambridge Repository, and Internal Medicine

Subjects
medicine.medical_specialty, Consensus, Medical therapy, Endocrinology, Diabetes and Metabolism, media_common.quotation_subject, education, 030209 endocrinology & metabolism, Article, Neurosurgical Procedures, 03 medical and health sciences, 0302 clinical medicine, Endocrinology, Multidisciplinary approach, Excellence, Acromegaly, Multidisciplinary management, Humans, Medicine, Medical physics, Pituitary tumor centers of excellence, media_common, Patient Care Team, Modalities, Radiotherapy, business.industry, Consensus conference, Treatment options, Expert consensus, Receptors, Somatotropin, medicine.disease, Dopamine Agonists, Practice Guidelines as Topic, Surgery, Somatostatin, business
Abstract

The 13th Acromegaly Consensus Conference was held in November 2019 in Fort Lauderdale, Florida, and comprised acromegaly experts including endocrinologists and neurosurgeons who considered optimal approaches for multidisciplinary acromegaly management. Focused discussions reviewed techniques, results, and side effects of surgery, radiotherapy, and medical therapy, and how advances in technology and novel techniques have changed the way these modalities are used alone or in combination. Effects of treatment on patient outcomes were considered, along with strategies for optimizing and personalizing therapeutic approaches. Expert consensus recommendations emphasize how best to implement available treatment options as part of a multidisciplinary approach at Pituitary Tumor Centers of Excellence.

Published
2020

36. A consensus on the diagnosis and treatment of acromegaly comorbidities

Author

Andrea Giustina, Annamaria Colao, Felipe F. Casanueva, Moisés Mercado, Diego Ferone, Laurence Katznelson, Albert Beckers, Stephan Petersenn, Pietro Maffei, Ken K. Y. Ho, Roberto Salvatori, Maria Chiara Zatelli, Fahrettin Kelestimur, Sebastian J C M M Neggers, Marco Losa, Pietro Mortini, Alberto M. Pereira, Steven W. J. Lamberts, Adriana G. Ioachimescu, Nienke R. Biermasz, John J. Kopchick, Christian J. Strasburger, Ariel L. Barkan, John A.H. Wass, Mónica Marazuela, Manel Puig-Domingo, Marcello D. Bronstein, Stefano Frara, Marek Bolanowski, David R. Clemmons, Stylianos Tsagarakis, Mônica R. Gadelha, Shlomo Melmed, Ilan Shimon, A. J. van der Lely, Anton Luger, Maria Fleseriu, Michal Krsek, Cesar Luiz Boguszewski, Beverly M. K. Biller, Mark Gurnell, Ezio Ghigo, Gherardo Mazziotti, Anthony P. Heaney, Vivien Bonert, Giustina, A., Barkan, A., Beckers, A., Biermasz, N., Biller, B. M. K., Boguszewski, C., Bolanowski, M., Bonert, V., Bronstein, M. D., Casanueva, F. F., Clemmons, D., Colao, A., Ferone, D., Fleseriu, M., Frara, S., Gadelha, M. R., Ghigo, E., Gurnell, M., Heaney, A. P., Ho, K., Ioachimescu, A., Katznelson, L., Kelestimur, F., Kopchick, J., Krsek, M., Lamberts, S., Losa, M., Luger, A., Maffei, P., Marazuela, M., Mazziotti, G., Mercado, M., Mortini, P., Neggers, S., Pereira, A. M., Petersenn, S., Puig-Domingo, M., Salvatori, R., Shimon, I., Strasburger, C., Tsagarakis, S., van der Lely, A. J., Wass, J., Zatelli, M. C., Melmed, S., Gurnell, Mark [0000-0001-5745-6832], Apollo - University of Cambridge Repository, and Internal Medicine

Subjects
medicine.medical_specialty, Consensus, diagnosis, Endocrinology, Diabetes and Metabolism, Clinical Biochemistry, Comorbidity, comorbidities, Biochemistry, NO, Comorbidities, Endocrinology, Quality of life (healthcare), Multidisciplinary approach, Internal medicine, Acromegaly, Diagnosis, medicine, Humans, LS4_3, Grading (education), treatment, business.industry, Biochemistry (medical), Sleep apnea, acromegaly, consensus, medicine.disease, Quality of evidence, Treatment, Current practice, Family medicine, Practice Guidelines as Topic, Quality of Life, Joint disorder, business
Abstract

Objective The aim of the Acromegaly Consensus Group was to revise and update the consensus on diagnosis and treatment of acromegaly comorbidities last published in 2013. Participants The Consensus Group, convened by 11 Steering Committee members, consisted of 45 experts in the medical and surgical management of acromegaly. The authors received no corporate funding or remuneration. Evidence This evidence-based consensus was developed using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) system to describe both the strength of recommendations and the quality of evidence following critical discussion of the current literature on the diagnosis and treatment of acromegaly comorbidities. Consensus Process Acromegaly Consensus Group participants conducted comprehensive literature searches for English-language papers on selected topics, reviewed brief presentations on each topic, and discussed current practice and recommendations in breakout groups. Consensus recommendations were developed based on all presentations and discussions. Members of the Scientific Committee graded the quality of the supporting evidence and the consensus recommendations using the GRADE system. Conclusions Evidence-based approach consensus recommendations address important clinical issues regarding multidisciplinary management of acromegaly-related cardiovascular, endocrine, metabolic, and oncologic comorbidities, sleep apnea, and bone and joint disorders and their sequelae, as well as their effects on quality of life and mortality.

Published
2020

37. Long-acting pasireotide improves clinical signs and quality of life in Cushing’s disease: results from a phase III study

Author

Ariel L. Barkan, Marcello D. Bronstein, T. Delibasi, S. Petersenn, Shoba Ravichandran, Rosario Pivonello, Roberto Salvatori, Jochen Schopohl, N. Suzaki, André Lacroix, C.-E. Ortmann, Libuse Tauchmanova, Yixue Li, Lacroix, A., Bronstein, M. D., Schopohl, J., Delibasi, T., Salvatori, R., Li, Y., Barkan, A., Suzaki, N., Tauchmanova, L., Ortmann, C. -E., Ravichandran, S., Petersenn, S., and Pivonello, R.

Subjects
Adult, Male, medicine.medical_specialty, Waist, Hydrocortisone, Endocrinology, Diabetes and Metabolism, Health-related quality of life, Hypercortisolism, 030209 endocrinology & metabolism, Blood Pressure, Disease, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, Endocrinology, Quality of life, Internal medicine, Medicine, Humans, Pituitary ACTH Hypersecretion, Cushing Syndrome, Aged, business.industry, Cushing's disease, Middle Aged, Cushing’s disease, medicine.disease, Pasireotide, Blood pressure, Treatment Outcome, Tolerability, chemistry, 030220 oncology & carcinogenesis, Delayed-Action Preparations, Quality of Life, Female, business, Somatostatin, Psychosocial
Abstract

Purpose: Cushing’s disease (CD) is associated with significant clinical burden, increased mortality risk, and impaired health-related quality of life (HRQoL). This analysis explored the effect of long-acting pasireotide on clinical signs of hypercortisolism and HRQoL in a large subset of patients with CD. Methods: In this phase III study (clinicaltrials.gov: NCT01374906), 150 adults with CD and a mean urinary free cortisol (mUFC) level between 1.5 and 5.0 times the upper limit of normal (ULN) started long-acting pasireotide 10 or 30 mg every 28 days with dose increases/decreases permitted based on mUFC levels/tolerability (minimum/maximum dose: 5/40 mg). Changes in clinical signs of hypercortisolism and HRQoL were assessed over 12 months of treatment and were stratified by degree of mUFC control for each patient. Results: Patients with controlled mUFC at month 12 (n = 45) had the greatest improvements from baseline in mean systolic (− 8.4 mmHg [95% CI − 13.9, − 2.9]) and diastolic blood pressure (− 6.0 mmHg [− 10.0, − 2.0]). Mean BMI, weight, and waist circumference improved irrespective of mUFC control. Significant improvements in CushingQoL total score of 5.9–8.3 points were found at month 12 compared with baseline, irrespective of mUFC control; changes were driven by improvements in physical problem score, with smaller improvements in psychosocial score. Conclusions: Long-acting pasireotide provided significant improvements in clinical signs and HRQoL over 12 months of treatment, which, in some cases, occurred regardless of mUFC control. Long-acting pasireotide represents an effective treatment option and provides clinical benefit in patients with CD. Clinical trial registration number: NCT01374906

Published
2020

38. Staging and managing patients with acromegaly in clinical practice: baseline data from the SAGIT® validation study

Author

Aude Houchard, Marcello D. Bronstein, Stephan Petersenn, Philippe Chanson, Caroline Sert, Felipe F. Casanueva, Shlomo Melmed, Andrea Giustina, Giustina, A., Bronstein, M. D., Chanson, P., Petersenn, S., Casanueva, F. F., Sert, C., Houchard, A., and Melmed, S.

Subjects
Adult, Male, medicine.medical_specialty, Validation study, Acromegaly control, Endocrinology, Diabetes and Metabolism, 030209 endocrinology & metabolism, Pilot Projects, Disease, Article, 03 medical and health sciences, 0302 clinical medicine, Endocrinology, Acromegaly management, Internal medicine, Surveys and Questionnaires, Acromegaly, medicine, Humans, Stage (cooking), Insulin-Like Growth Factor I, Aged, business.industry, Human Growth Hormone, Baseline data, Middle Aged, medicine.disease, Interim analysis, Clinical Practice, SAGIT® instrument, Concomitant, Female, business, Clinician-reported outcomes, 030217 neurology & neurosurgery
Abstract

Purpose The SAGIT® instrument, designed to assist clinicians to stage acromegaly, assess treatment response and adapt patient management, was well received by endocrinologists in a pilot study. We report an interim analysis of baseline data from the validation phase. Methods The SAGIT® validation study (ClinicalTrials.gov NCT02539927) is an international, non-interventional study. Data collection included: demographic/disease characteristics; medical/surgical histories; concomitant acromegaly treatments; investigators’ subjective evaluation of disease-control status (clinical global evaluation of disease control [CGE-DC]; controlled/not controlled/yet to be clarified) and clinical disease activity (active/not active); growth hormone (GH) and insulin-like growth factor-1 (IGF-1) levels; investigators’ therapeutic decision. Results Of 228 patients enrolled, investigators considered disease to be controlled in 110 (48.2%), not controlled in 105 (46.1%), and yet to be clarified in 13 (5.7%) according to CGE-DC. Thirty-three patients were treatment-naïve (not controlled, n = 31; yet to be clarified, n = 2). Investigators considered 48.2% patients in the controlled and 95.2% in the not-controlled groups to have clinically active disease. In the controlled group, 29.7% of patients did not exhibit hormonal control (GH ≤ 2.5 µg/L; normalized IGF-1) and 47.3% did not have rigorous hormonal control (GH Conclusions These data highlight discrepancies between investigator-evaluated disease-control status, disease activity, hormonal control, and treatment decisions in acromegaly. Once validated, the SAGIT® instrument may assist clinicians in making active management decisions for patients with acromegaly.

Published
2019

39. GFrames: gradient-based local reference frame for 3d shape matching

Author

Simone Melzi, Michael M. Bronstein, Emanuele Rodolà, Riccardo Spezialetti, Luigi Di Stefano, Federico Tombari, Melzi, S, Spezialetti, R, Tombari, F, Bronstein, M, Di Stefano, L, Rodolà, E, S. Melzi, R. Spezialetti, F. Tombari, M. M. Bronstein, L. Di Stefano, and E. Rodolà

Subjects
local reference frame, Computer science, Motion and Tracking, shape analysis, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Point cloud, 02 engineering and technology, 3D from Multiview and Sensor, 3D meshes, Recognition: Detection, shape descriptor. gradient, Low-level Vision, 0202 electrical engineering, electronic engineering, information engineering, Polygon mesh, Tangent vector, ComputingMethodologies_COMPUTERGRAPHICS, shape matching, Retrieval, business.industry, Tangent, 020207 software engineering, Local reference frame, Categorization, 020201 artificial intelligence & image processing, Artificial intelligence, business, shape analysis, shape matching, local reference frame, shape descriptor. gradient, Algorithm, Scalar field, Shape analysis (digital geometry)
Abstract

We introduce GFrames, a novel local reference frame (LRF) construction for 3D meshes and point clouds. GFrames are based on the computation of the intrinsic gradient of a scalar field defined on top of the input shape. The resulting tangent vector field defines a repeatable tangent direction of the local frame at each point; importantly, it directly inherits the properties and invariance classes of the underlying scalar function, making it remarkably robust under strong sampling artifacts, vertex noise, as well as non-rigid deformations. Existing local descriptors can directly benefit from our repeatable frames, as we showcase in a selection of 3D vision and shape analysis applications where we demonstrate state-of-the-art performance in a variety of challenging settings.

Published
2019

40. Improved functional mappings via product preservation

Author

Dorian Nogneng, Michael M. Bronstein, Maks Ovsjanikov, Simone Melzi, Umberto Castellani, Emanuele Rodolà, Laboratoire d'informatique de l'École polytechnique [Palaiseau] (LIX), Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X), Department of Computer Science [Verona] (UNIVR | DI), University of Verona (UNIVR), Department of Informatics and System Sciences (Sapienza University of Rome), Università degli Studi di Roma 'La Sapienza' = Sapienza University [Rome], Università della Svizzera italiana = University of Italian Switzerland (USI), Nogneng, D, Melzi, S, Rodolá, E, Castellani, U, Bronstein, M, and Ovsjanikov, M

Subjects
Pointwise, Shape analysi, Basis (linear algebra), Computational complexity theory, Computer science, shape analysis, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], Software Engineering, products preservation, 020207 software engineering, Basis function, 02 engineering and technology, Function (mathematics), functional mapping, Computer Graphics and Computer-Aided Design, Computational geometry, 0202 electrical engineering, electronic engineering, information engineering, 0801 Artificial Intelligence and Image Processing, Shape analysis, Theory of computation, 020201 artificial intelligence & image processing, Representation (mathematics), Linear combination, Algorithm, Vector space
Abstract

International audience; In this paper, we consider the problem of information transfer across shapes and propose an extension to the widely used functional map representation. Our main observation is that in addition to the vector space structure of the functional spaces, which has been heavily exploited in the functional map framework, the functional algebra (i.e., the ability to take pointwise products of functions) can significantly extend the power of this framework. Equipped with this observation, we show how to improve one of the key applications of functional maps, namely transferring real-valued functions without conversion to point-to-point correspondences. We demonstrate through extensive experiments that by decomposing a given function into a linear combination consisting not only of basis functions but also of their pointwise products, both the representation power and the quality of the function transfer can be improved significantly. Our modification, while computationally simple, allows us to achieve higher transfer accuracy while keeping the size of the basis and the functional map fixed. We also analyze the computational complexity of optimally representing functions through linear combinations of products in a given basis and prove NP-completeness in some general cases. Finally, we argue that the use of function products can have a wide-reaching effect in extending the power of functional maps in a variety of applications, in particular by enabling the transfer of high-frequency functions without changing the representation size or complexity.

Published
2018

41. Shape analysis with anisotropic windowed Fourier transform

Author

Emanuele Rodolà, Umberto Castellani, Simone Melzi, Michael M. Bronstein, Melzi, S, Rodola, E, Castellani, U, and Bronstein, M

Subjects
Signal processing, Standards, Non-uniform discrete Fourier transform, Manifolds, Laplace equations, Shape, Eigenvalues and eigenfunctions, Fourier transforms, Standards, Signal processing, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, 02 engineering and technology, symbols.namesake, 0202 electrical engineering, electronic engineering, information engineering, 3D shape, Shape analysis, Windowed Fourier Transform, Laplace equations, Manifolds, ComputingMethodologies_COMPUTERGRAPHICS, Mathematics, Sine and cosine transforms, Eigenvalues and eigenfunctions, Shape analysi, business.industry, Mathematical analysis, Fourier inversion theorem, Short-time Fourier transform, Shape, 020207 software engineering, Fractional Fourier transform, Fourier transforms, Fourier transform, Fourier analysis, symbols, 020201 artificial intelligence & image processing, Artificial intelligence, business, Algorithm, Shape analysis (digital geometry)
Abstract

We propose Anisotropic Windowed Fourier Transform (AWFT), a framework for localized space-frequency analysis of deformable 3D shapes. With AWFT, we are able to extract meaningful intrinsic localized orientation-sensitive structures on surfaces, and use them in applications such as shape segmentation, salient point detection, feature point description, and matching. Our method outperforms previous approaches in the considered applications.

Published
2016

42. Learning class-specific descriptors for deformable shapes using localized spectral convolutional networks

Author

Jonathan Masci, Pierre Vandergheynst, Umberto Castellani, Michael M. Bronstein, Davide Boscaini, Simone Melzi, Boscaini, D, Masci, J, Melzi, S, Bronstein, M, Castellani, U, and Vandergheynst, P

Subjects
spectral shape analysis, Frequency analysis, Computational Geometry and Object Modeling [I.3.5], Shape matching, Laplace Beltrami, Windowed Fourier Transform, Convolutional Neural Network, Shape matching, spectral shape analysis, Laplace Beltrami, Windowed Fourier Transform, Convolutional Neural Network, Generalization, business.industry, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Windowed fourier transform, Feature Measurement [I.4.7], Computer Graphics and Computer-Aided Design, Convolutional neural network, Class (biology), law.invention, law, Learning [I.2.6], Global Positioning System, Categories and Subject Descriptors (according to ACM CCS), business, Algorithm, Mathematics
Abstract

In this paper, we propose a generalization of convolutional neural networks (CNN) to non-Euclidean domains for the analysis of deformable shapes. Our construction is based on localized frequency analysis (a generalization of the windowed Fourier transform to manifolds) that is used to extract the local behavior of some dense intrinsic descriptor, roughly acting as an analogy to patches in images. The resulting local frequency representations are then passed through a bank of filters whose coefficient are determined by a learning procedure minimizing a task-specific cost. Our approach generalizes several previous methods such as HKS, WKS, spectral CNN, and GPS embeddings. Experimental results show that the proposed approach allows learning class-specific shape descriptors significantly outperforming recent state-of-the-art methods on standard benchmarks.

Published
2015

43. Fast 3-D Urban Object Detection on Streaming Point Clouds

Author

Attila Börcs, Balázs Nagy, Csaba Benedek, Lourdes, Agapito, Bronstein, M M, and Carsten, Rother

Subjects
Lidar, business.industry, Computer science, Real-time computing, Point cloud, Computer vision, QA75 Electronic computers. Computer science / számítástechnika, számítógéptudomány, Artificial intelligence, business, Pipeline (software), Connected-component labeling, Object detection
Abstract

Efficient and fast object detection from continuously streamed 3-D point clouds has a major impact in many related research tasks, such as autonomous driving, self localization and mapping and understanding large scale environment. This paper presents a LIDAR-based framework, which provides fast detection of 3-D urban objects from point cloud sequences of a Velodyne HDL-64E terrestrial LIDAR scanner installed on a moving platform. The pipeline of our framework receives raw streams of 3-D data, and produces distinct groups of points which belong to different urban objects. In the proposed framework we present a simple, yet efficient hierarchical grid data structure and corresponding algorithms that significantly improve the processing speed of the object detection task. Furthermore, we show that this approach confidently handles streaming data, and provides a speedup of two orders of magnitude, with increased detection accuracy compared to a baseline connected component analysis algorithm.

Published
2014

44. Pasireotide versus octreotide in acromegaly: A head-to-head superiority study

Author

Mônica R. Gadelha, Matthieu Ruffin, Pamela U. Freda, Annamaria Colao, YinMiao Chen, C. Shen, Andrew J. Farrall, Maria Fleseriu, Marcello D. Bronstein, Michael C. Sheppard, K. Hermosillo Reséndiz, Feng Gu, A. J. van der Lely, Colao, Annamaria, Bronstein, M. D., Freda, P., Gu, F., Shen, C. C., Gadelha, M., Fleseriu, M., Van Der Lely, A. J., Farrall, A. J., Hermosillo Reséndiz, K., Ruffin, M., Chen, Y., Sheppard, M., and Internal Medicine

Subjects
Adenoma, Adult, Male, medicine.medical_specialty, Adolescent, Antineoplastic Agents, Hormonal, Endocrinology, Diabetes and Metabolism, Clinical Biochemistry, Octreotide, Context (language use), Biochemistry, law.invention, chemistry.chemical_compound, Young Adult, Endocrinology, SDG 3 - Good Health and Well-being, Randomized controlled trial, law, Pituitary adenoma, Internal medicine, Acromegaly, medicine, Humans, Aged, Aged, 80 and over, Endocrine Care, business.industry, Biochemistry (medical), Middle Aged, medicine.disease, Pasireotide, chemistry, Tolerability, Therapeutic Equivalency, Female, Growth Hormone-Secreting Pituitary Adenoma, business, Somatostatin, medicine.drug, Human
Abstract

Context: Biochemical control reduces morbidity and increases life expectancy in patients with acromegaly. With current medical therapies, including the gold standard octreotide long-acting-release (LAR), many patients do not achieve biochemical control. Objective: Our objective was to demonstrate the superiority of pasireotide LAR over octreotide LAR in medically naive patients with acromegaly. Design and Setting: We conducted a prospective, randomized, double-blind study at 84 sites in 27 countries. Patients: A total of 358 patients with medically naive acromegaly (GH > 5 mu g/L or GH nadir >= 1 mu g/L after an oral glucose tolerance test (OGTT) and IGF-1 above the upper limit of normal) were enrolled. Patients either had previous pituitary surgery but no medical treatment or were de novo with a visible pituitary adenoma on magnetic resonance imaging. Interventions: Patients received pasireotide LAR 40 mg/28 days (n = 176) or octreotide LAR 20 mg/28 days (n = 182) for 12 months. At months 3 and 7, titration to pasireotide LAR 60 mg or octreotide LAR 30 mg was permitted, but not mandatory, if GH >= 2.5 mu g/L and/or IGF-1 was above the upper limit of normal. Main Outcome Measure: The main outcome measure was the proportion of patients in each treatment arm with biochemical control (GH

Published
2014

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