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10 results on '"Gero, L."'

1. Towards a more realistic simulation of public transit: Generating transit schedules with vehicle circulations

Author

Gero L. Marburger and Ihab Kaddoura

Subjects
business.industry, Computer science, computer.file_format, Turnaround time, Data conversion, Reduction (complexity), Public transport, General Earth and Planetary Sciences, ddc:004, business, Transit (satellite), computer, Simulation, General Environmental Science
Abstract

In this study, two approaches are presented to account for vehicle circulations when incorporating GTFS data into the agent-based simulation framework MATSim. The first approach directly builds on an existing data converter; the second approach integrates the external public transit planning tool LinTim into MATSim. Both proposed methodological approaches are successfully used to generate transit schedules with vehicle circulations. Simulation experiments are carried out for the Greater Berlin area and reveal an overall minor impact on the public transit performance from the transport users’ perspective. The number of required public transit vehicles is significantly reduced compared to previous version of the GTFS data converter. Reducing the turnaround time leads to a further reduction in vehicles, however, provides reduced slack times to compensate for delays. The implementation of a disruption shows that the bunching phenomenon and delay propagation is now represented by the model. Thus, the proposed methodology allows for a more sophisticated investigation of transit schedules and delay management concepts.

Published
2021

2. Effect of Sibutramine on Cardiovascular Outcomes in Overweight and Obese Subjects

Author

James, Wp, Caterson, Id, Coutinho, W, Finer, N, VAN GAAL LF, Maggioni, Ap, TORP-PEDERSEN, C, Sharma, Am, Shepherd, Gm, Rode, Ra, Renz, Cl, Van Gaal LF, Torp-Pedersen, C, Pepine, C, Pocock, S, Drexler, H, Swedberg, K, Sleight, P, Armstrong, P, Kerr, D, Dagenais, G, Brophy, J, Avezum, A, Bogaty, P, Fabbri, G, Galli, M, Hildebrandt, P, Mann, J, Ostergren, J, Sherman, D, Zannad, F, Colquhoun, D, Hollanders, G, e Forti A, Costa, Cifkova, R, Toubro, S, Ziegler, O, Scherbaum, Wa, Jordan, J, Halmy, L, Ferrannini, E, Santini, F, Gonzalez, C, Narkiewicz, K, Hancu, N, Payer, J, Pascual, J, Wilding, J, Campbell, L, Carey, D, Gerstman, M, Karrasch, J, Lefkovits, J, Marks, J, Marks, S, Moses, R, Phillips, P, Proietto, J, Roberts, D, Roberts-Thomson, P, Shaw, J, Simpson, R, Singh, B, Singleton Jeffries, W, Stuckey, B, Boland, J, Brohet, C, Coucke, F, Dendale, P, Jouret, G, Kolanowski, J, Kutnowski, M, Martens, F, Muls, E, Peiffer, F, Penninckx, H, Scheen, A, Schoors, D, Vaerenberg, M, Van Cleemput, J, Van Crombrugge, P, Van Kuyk, M, Verhaegen, A, Wollaert, B, de Albuquerque DC, Appolinario, J, de Godoy Matos AF, Gross, Jl, Halpern, A, Kerr Saraiva JF, Milagres, R, Repetto, G, Suplicy, Hl, Zanella, Mt, Bednarova, J, Cepelak, V, Cerny, P, Hainer, V, Havranek, P, Homza, M, Jansa, P, Karlicek, M, Kolesar, J, Kotik, I, Kucera, D, Kuchar, J, Kunc, M, Kvapil, M, Linhart, A, Machova, V, Matuska, J, Oral, I, Pavlas, J, Pesatova, S, Povolny, J, Semrad, B, Smetana, K, Soucek, M, Svacina, S, Tesinsky, P, Urbanek, R, Wasserburger, B, Zachoval, R, Zahumensky, E, Zidkova, E, Astrup, A, Dominguez, H, Faber, J, Hilderbrant, P, Kober, L, Perrild, H, Richelsen, B, Sogaard, P, Svendsen, Ol, Urhammer, S, Archambeaud, F, Basdevant, A, Borys, Jm, Bringer, J, Brunetiere, C, Charpentier, G, Cocaul-André, M, Dabadie, H, Dubreuil, A, Estour, B, Gautier, Jf, Gibault, T, Halimi, S, Hespel, Jp, Issa Sayegh, M, Krempf, M, Laville, M, Lecerf, Jm, Louvet, Jp, Penfornis, A, Ritz, P, Schlienger, Jl, Schmitt, B, Valensi, P, Baar, M, Beermann, J, Bock, M, Boenner, G, Dammann, Hg, Diehm, C, Ditschuneit, H, Gadow, J, Gehlhar, S, Gessner, S, Guthersohn, A, Hamann, A, Hanefeld, M, Hasenfuss, G, Herzner, A, Heun, Kc, Heufelder, Ae, Hohensee, H, Jacob, S, Krings, P, Krätzig, B, Krosse, B, Lehmann, Rt, Mindt-Prüfert, S, Maisch, B, Pfeiffer, Af, Richard, F, Rose, B, Schmidt, E, Scholze, J, Schreckenberg, A, Stuebler, P, Walter, J, Wirth, A, Wunderlich, J, Abraham, G, Altorjay, A, Augusztin, G, Csaszar, A, Czuriga, I, Dinnyes, J, Gero, L, Gyimesi, A, Janosi, A, Kovacs, I, Liziczai, I, Majtenyi, A, Medvegy, M, Nadhazi, Z, Pados, G, Polak, G, Ronaszeki, A, Sido, Z, Simon, K, Anzà, C, Bevilacqua, M, Bosello, O, Chiariello, M, Cordera, R, Ferrari, E, Frittitta, L, Giorgino, R, Liuzzi, A, Malinverni, C, Di Mario, U, Melchionda, N, Occhi, G, Perticone, F, Pinchera, A, Pinelli, G, Rovera, G, Santeusanio, F, Urbinati, S, Alpizar-Salazar, M, Carrillo-Ortega, E, Fanghanel Salmon, G, Laviada-Molina, Ha, Madero, Ma, Rodriguez, G, Saldate, C, Sanchez-Castillo, Cp, Violante, Rm, Wacher, N, Zayas-Jaime, Fj, Zuniga-Guajardo, S, Adamiec, R, Banasiak, W, Chrusciel, P, Derlaga, B, Gebala, A, Gessek, J, Janik, K, Janion, M, Kalina, Z, Kozlowski, A, Kusnierz, B, Majcher, Z, Miekus, P, Niegowska, J, Okopien, B, Ostrowska, L, Pasowicz, M, Piepiorka, M, Pluta, W, Polaszewska-Muszynska, M, Ponikowski, P, Pupek-Musialik, D, Sawicki, A, Sobocik, H, Stankiewicz, A, Szpajer, M, Trojnar, R, Tykarski, A, Wrabec, K, Wyrzkowski, B, Zahorska-Markiewicz, B, Zalewski, M, Carrageta, M, Mendes Pedro MM, Parente Martins LM, dos Santos, L, Babes, A, Creteanu, G, Dan, Ga, Dragulescu, Si, Graur, M, Tirgoviste, Ci, Morosanu, M, Mota, M, Paveliu, Fs, Radoi, M, Ranetti, A, Totoian, I, Andre, I, Bugan, V, Cencarik, J, Csala, L, Farsky, S, Gonsorcik, J, Kamensky, G, Kmec, J, Krahulec, B, Kurian, R, Macek, V, Majercak, I, Micko, K, Mokan, M, Riecansky, I, Sojka, G, Uhliar, R, Urgeova, L, Vancik, J, Baro, Fm, Barrios Merino, A, Borras, Jl, Caixas, A, Cuatrecasas Cambra, G, Dominguez Escribano JR, Duran Garcia, S, Escobar-Jimenez, L, Esteva de Antonio, I, Formiguera Sala, X, Garcia-Luna, Pp, Garcia Robles, R, Gonzalez Albarran, O, Hernandez-Mijares, A, Martin Hidalgo, A, Masmiquel Comas, L, Morales Perez, F, Moreno Esteban, B, Pascual Izuel JM, Redon Mas, J, Ricart, W, Rubio, Ma, Ruilope, Lm, Salas-Salvado, J, Terroba Larumbe, M, Tinahones, F, de la Torre Casares ML, Vidal Cortada, J, Zuniga-Perez Lemaur, M, Abdulhakim, Ee, Adler, A, Barnett, Ah, Bodmer, C, Campbell, Iw, Chowdhury, T, Cleland, J, Cook, Rc, Dinneen, S, Donnachie, H, Haslam, Dw, Hillis, Gs, Horne, M, Howarth, Dj, Hughes, E, Jackson, S, Jones, Sc, Jones, Th, Kumar, S, Lean, M, Maroni, J, Mcinnes, G, Middleton, A, Morris, A, Newcombe, G, O'Kane, Kp, Pavel, Ic, Pawa, R, Perry, C, Pitts, C, Raja, A, Reckless, J, Robinson, J, Sarmiento, R, Soo, Sc, Taylor, S, Thomas, Ho, Thomson, Ma, and Wilkins, M.

Subjects
Male, medicine.medical_specialty, Myocardial Infarction, Blood Pressure, Kaplan-Meier Estimate, Type 2 diabetes, Klinikai orvostudományok, Placebo, law.invention, Double-Blind Method, Randomized controlled trial, Weight loss, law, Internal medicine, Appetite Depressants, medicine, Humans, Obesity, Myocardial infarction, Stroke, Aged, business.industry, Hazard ratio, Orvostudományok, General Medicine, Middle Aged, Overweight, medicine.disease, Surgery, Diabetes Mellitus, Type 2, Cardiovascular Diseases, Cardiology, Female, Human medicine, medicine.symptom, business, Cyclobutanes, Sibutramine, medicine.drug
Abstract

Background The long-term effects of sibutramine treatment on the rates of cardiovascular events and cardiovascular death among subjects at high cardiovascular risk have not been established. Methods We enrolled in our study 10,744 overweight or obese subjects, 55 years of age or older, with preexisting cardiovascular disease, type 2 diabetes mellitus, or both to assess the cardiovascular consequences of weight management with and without sibutramine in subjects at high risk for cardiovascular events. All the subjects received sibutramine in addition to participating in a weight-management program during a 6-week, single-blind, lead-in period, after which 9804 subjects underwent random assignment in a double-blind fashion to sibutramine (4906 subjects) or placebo (4898 subjects). The primary end point was the time from randomization to the first occurrence of a primary outcome event (nonfatal myocardial infarction, nonfatal stroke, resuscitation after cardiac arrest, or cardiovascular death). Results The mean duration of treatment was 3.4 years. The mean weight loss during the lead-in period was 2.6 kg; after randomization, the subjects in the sibutramine group achieved and maintained further weight reduction (mean, 1.7 kg). The mean blood pressure decreased in both groups, with greater reductions in the placebo group than in the sibutramine group (mean difference, 1.2/1.4 mm Hg). The risk of a primary outcome event was 11.4% in the sibutramine group as compared with 10.0% in the placebo group (hazard ratio, 1.16; 95% confidence interval [CI], 1.03 to 1.31; P=0.02). The rates of nonfatal myocardial infarction and nonfatal stroke were 4.1% and 2.6% in the sibutramine group and 3.2% and 1.9% in the placebo group, respectively (hazard ratio for nonfatal myocardial infarction, 1.28; 95% CI, 1.04 to 1.57; P=0.02; hazard ratio for nonfatal stroke, 1.36; 95% CI, 1.04 to 1.77; P=0.03). The rates of cardiovascular death and death from any cause were not increased. Conclusions Subjects with preexisting cardiovascular conditions who were receiving long-term sibutramine treatment had an increased risk of nonfatal myocardial infarction and nonfatal stroke but not of cardiovascular death or death from any cause. (Funded by Abbott; ClinicalTrials.gov number, NCT00234832.)

Published
2010
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3. Cardiorenal End Points in a Trial of Aliskiren for Type 2 Diabetes

Author

Parving, Hh, Brenner, Bm, Mcmurray, Jj, de Zeeuw, D, Haffner, Sm, Solomon, Sd, Chaturvedi, N, Persson, F, Desai, As, Nicolaides, M, Richard, A, Xiang, Z, Brunel, P, Pfeffer, Ma, Viberti, G, Lachin, Jm, Zinman, B, Pedersen, Tr, Villamil, As, Juncos, L, Prager, R, Verpooten, G, Zanella, Mt, Leiter, L, Pan, C, Wang, H, Botero, R, Cifkova, R, Christiansen, Js, Groop, Ph, Marre, M, Haller, H, Nickenig, G, Siamopoulos, K, Gero, L, Maggioni, A, Remuzzi, G, Katayama, Ss, Kim, Sg, Petrulioniene, Z, Lok, D, Kooy, A, Jorde, R, Medina, F, Polonia, J, Wong, Ks, Dukat, A, Rayner, Bl, Ruilope, L, Weiss, L, Wuethrich, R, Sheu, W, Sritara, P, Comlekci, A, Bilous, R, Toto, R, Jamerson, K, Carillo, E, Orias, M, Kuschnir, E, Rusculleda, M, Garcia, S, Farias, E, Lema, L, Hominal, M, Montaña, O, Sala, J, Diaz, M, Piskorz, D, Vita, N, Litwak, L, Sinay, I, Marin, M, Massari, P, Majul, C, Aizemberg, D, Azize, Gm, Bartolacci, I, Reboredo, A, Vico, M, Milesi, R, Sessa, H, Wassermann, A, Margulis, F, Zangroniz, P, Watschinger, B, Toplak, H, Paulweber, B, Drexel, H, Francesconi, C, Foeger, B, Mayer, G, Braun, Rk, Brath, H, Gaal, Lv, Niepen, Pv, Persu, A, Vercammen, C, Vriese, Ad, Coucke, F, Mathieu, C, Fery, F, Treille, S, Meeus, G, Acker, Kv, Scheen, A, Tits, J, Ruige, J, Krzesinski, Jm, Hollanders, G, Liénart, F, Dendale, P, Quinonez, M, Arnouts, P, Vanuytsel, J, Zanella, M, Mion D., Jr, Forti, A, Almeida, F, Cunha, R, de Paula RB, Brandao, A, Rocha, J, Krieger, E, Feitosa, G, Saraiva, J, Martin, J, Hissa, Mn, Schmid, H, Felicio, J, Sgarbi, J, Oigman, W, Bowering, K, Garceau, C, Berlingieri, Jc, Weisnagel, Sj, Hardin, P, Powell, C, Turcot, R, Muirhead, N, Aronson, R, Barima, Yt, Steele, Aw, Pandey, S, Woo, V, Cha, J, Dattani, D, Godin, C, Gupta, M, Saunders, K, Tellier, G, Ting, R, Tobe, S, Chouinard, G, Schlosser, R, Khandwala, H, Ekoe, Jm, Harris, Sb, Pichette, V, Lachance, P, Ooi, Tc, Tildesley, H, Barrett, B, Cournoyer, S, Lu, J, Zhang, H, Liu, X, Yan, S, Qi, X, Li, Q, Li, H, Lv, X, Yang, J, Sun, N, Xia, W, Wang, N, Tong, N, Mei, C, Gu, S, Zhang, J, Chen, X, Li, L, Su, B, Wang, L, Qiu, M, Wu, X, Liu, Z, Jia, W, Xu, G, Dong, J, Zhu, D, Zhang, M, Yan, J, Liu, B, Chen, J, Fu, J, Yan, L, Zhan, X, Zhong, L, Yang, T, Ma, J, Xu, M, Xu, X, Shi, B, Ji, Q, Zhong, H, He, R, Yuan, Z, Zhou, Z, Lin, H, Yang, W, Ke, Y, Hong, T, Franco, C, Casas, L, Triana, A, Jaramillo, C, Hernandez, E, Barrera, C, Blanco, D, Stipal, R, Widimsky, P, Dohnalova, L, Komroskova, M, Kvapil, M, Belobradkova, J, Tesar, V, Vodnansky, P, Kocourkova, B, Lervang, Hh, Perrild, H, Rossing, P, Oestergaard, O, Juhl, H, Thorsteinsson, B, Snorgaard, O, Urhammer, S, Egstrup, K, Tikkanen, T, Helin, K, Rinne, J, Lahtela, J, Strand, J, Valtonen, E, Saari, M, Kananen, K, Savela, K, Blacher, J, Aldigier, Jc, Zaoui, P, Fauvel, Jp, Gouet, D, Valensi, Pe, Charpentier, G, Marechaud, R, Penfornis, A, Ovize, M, Kovalchuck, Aa, Dellanna, F, Schoen, N, Groeschel, W, Eickhoff, F, Hanefeld, M, Merke, J, Rambausek, M, Zimmermann, U, Stuetz, W, Vosskuehler, A, Hevendehl, G, Schax, U, Lehmann, G, Haack, A, Hilgenberg, J, Klausmann, G, Adelberger, V, Gessner, S, Fiesselmann, A, Oerter, E, Hohenstatt, T, Groeschel, A, Behnke, T, Sisting, Rt, Schoch, D, Bieler, T, Schleyer, S, Altes, U, Klepzig, C, Rudofsky, G, Mueller, G, Burkhardt, F, Reschke, K, Senftleber, I, Wiesweg, Ck, Herrmann, Hj, Brandstetter, R, Segner, A, Schmitt, H, Rippert, R, Goebel, R, Schreibmueller, F, Pencz, I, Ott, P, Migdalis, I, Pappas, S, Pagkalos, E, Yalouris, A, Tsapas, A, Maltezos, E, Tentolouris, N, Papadakis, I, Ioannidis, G, Goumenos, D, Corona, V, Gonzalez, R, Haase, F, Monterroso, V, Sánchez, V, Turcios, E, Wyss, F, Arango, Jl, Bako, B, Deak, L, Dömötör, E, Dudas, M, Fulop, T, Kiss, I, Koranyi, L, Lengyel, Z, Nyirati, G, Oroszlan, T, Aniko, S, Vörös, P, Kapocsi, J, Wittmann, I, Paragh, G, Abraham, G, Tandon, N, Thomas, N, Mohan, V, Sahay, R, Sethi, B, Rao, V, Kumar, S, Chowdhury, S, Dharmalingam, M, Seshiah, V, Bantwal, G, Viswanathan, V, Yajnik, C, Adhikari, P, Krishnan, U, Varthakavi, P, Hiremath, J, Bhattacharyya, A, Dani, S, Modi, Kk, Glorioso, N, Morosetti, M, Veglio, Franco, Perticone, F, Dotta, F, Quarello, F, Sesti, G, Aiello, A, D'Ospina, A, Giordano, C, Novo, S, Santoro, A, Ferri, C, Capuano, V, Trimarco, B, Tonolo, G, Villa, G, De Pellegrin, A, Zanette, G, Federici, M, Aucello, G, Piatti, P, Vinciguerra, A, Mannarino, E, Taddei, S, Filetti, S, Grandaliano, G, Marchionni, N, Lambiase, C, Locatelli, F, Scanferla, F, Lembo, G, Leotta, S, Mos, L, Calatola, P, Fogari, R, David, S, Pedrinelli, R, Pignone, Am, Cozzolino, D, Bevilacqua, Mt, Catena, C, Del Prato, S, Cerasola, G, Frontoni, S, Falcone, C, Porta, A, Bonora, E, Cocchi, R, Fucili, A, Frisinghelli, A, Volpe, M, Carugo, S, Gambardella, S, Spagnuolo, V, Maglia, G, D'Angelo, Ar, Corsi, A, Limone, Pp, Guarnieri, A, Ghigo, Ezio, Ronchi, E, Ravera, M, Scioli, Ga, Sekiguchi, M, Aoki, S, Ogawa, Y, Seino, H, Onishi, Y, Tojo, A, Narimiya, M, Iwaita, Y, Takeda, H, Shimizu, H, Yamada, T, Kojima, S, Zushi, S, Kaneko, S, Matsumoto, A, Kajiyama, S, Fujita, H, Shikata, K, Tone, A, Matsubayashi, S, Tanaka, S, Sekigami, T, Tatsukawa, Y, Abe, N, Kawahara, K, Kasahara, H, Maeda, Y, Suzuki, Y, Okamoto, H, Tachi, K, Yamada, K, Uzu, T, Itou, T, Fukui, T, Kim, S, Kim, Y, Cho, W, Kwak, I, Chae, D, Oh, H, Ha, S, Shin, Y, Cha, D, Kang, S, Lim, C, Song, J, Kwon, Y, Badariene, J, Labutiniene, Ip, Zabuliene, L, Poteliuniene, V, Miglinas, M, van den Meiracker AH, Gregoor, Pj, Luik, Aj, van Loon BJ, Feenstra, Hj, Kaasjager, Ha, Viergever, Pp, Woittiez, Aj, van Bemmel, T, Lieverse, Ag, Simsek, S, Gaillard, Ca, van der Zwaan, C, Lok, Dj, Spiering, W, Nierop, Pr, Baggen, Mg, Leendert, Rj, de Jong, A, Leurs, Pb, Vincent, Hh, Wins, Eh, Voors, Aa, Ronner, E, Heeg, Je, van Hal JM, Boermans, T, Feis, Wl, Mostard, G, Bakker, Rc, Dunselman, Ph, Skeie, S, Istad, H, Skjelvan, G, Gronert, J, Tomala, T, Gudnason, S, Torvik, Dt, Risberg, K, Abedini, S, Cabrera, W, Medina, B, Herrada, B, Saavedra, A, Polonia, Dj, Providencia, Dl, Carvalho, D, Vasconcelos, Mp, da Silva GF, Branco, P, Gil, Dv, da Costa AG, da Silva PM, Arez, L, Martins, L, Birne, R, Dzuponova, J, Surovcikova, M, Culak, J, Filipova, S, Andre, I, Stevlik, J, Uhliar, R, Fabryova, L, Benacka, J, Koleny, D, Szentivanyi, M, Spisak, V, Pella, D, Pastrnakova, E, Martinka, E, Chua, T, Lau, T, Ng, Tg, Yeoh, Ly, Bhana, Sa, Rayner, B, Wellmann, H, Amod, A, Ranjith, N, Ahmed, F, Rheeder, P, Makan, H, Naicker, P, Podgorski, G, De Teresa, E, Olivan, J, Fernandez, Vl, Povedano, St, Terns, M, Ricart, W, Gonzalez, Jm, Fernandez, P, Parreño Lde, T, Redon, J, Parra, J, Calvo, C, Lopez, I, Puig, Jg, Calle, A, Garcia, Jc, Lopez, Jm, Jimenez, Ml, Fraile, B, Perez, Js, Nadal, Jj, Guija, E, Calviño, J, Barrios, V, Iglesias, Jn, Armario, P, Garcia, M, Aranda, P, Brotons, C, Gomez, P, Catelao, Am, Cusachs, Ar, Sarro, M, Martinez, V, dell Valle MH, Trias, F, Comas, A, Salvador, N, Martinez, F, Hernandez, F, Martinez, J, Mateos, C, Peral, Jl, Tolosana, J, Sobrino, J, Isart, J, Vizcaino, J, Vega, Ff, Zamorano, Jl, Bacariza, M, Soubriet, A, Fernández Cruz, A, Querejeta, R, Leira, Vm, Iglesias, Fe, Ibrik, O, Martin, D, Nanclares, Ms, Mediavilla, Jd, Galceran, Jm, Lopez, A, Muros, T, Pascual, J, Casalla, F, Tornero, F, Fernandez, G, Pettersson, P, Olsen, H, Franke, F, Stroembom, U, Furuland, H, Larnefelt, H, Allemann, Y, Krapf, R, Gerber, P, Munger, R, Hayoz, D, Graf, Hj, Burnier, M, Petrillo, A, Batt, R, Constam, En, Moccetti, T, Bianda, T, Rickli, H, Bulliard, C, Wu, Kd, Lin, Sh, Wu, Cj, Sheu, Wh, Su, Sl, Chen, Sc, Chou, Cw, Lee, Ct, Yang, Tc, Chen, Hc, Sukonthasarn, A, Sriratanasathavorn, C, Eiam Ong, S, Supasyndh, O, Chanchairujira, T, Kitiyakara, C, Arici, M, Usalan, C, Guneri, S, Koc, M, Kalender, B, Ates, K, Gurgun, C, Araz, M, Demirbas, B, Biernacki, W, Calvert, J, Eavis, P, Kerrane, J, Litchfield, J, Middleton, A, Roberts, J, Simpson, H, Charles, H, Jardine, A, Fisher, M, Banerjee, D, Gallen, I, Gnudi, L, Harvey, J, O'Hare, P, Vora, J, Winocour, P, Soran, H, Browne, D, Darko, D, Mancebo, Jg, de Roa ER, Antepara, N, Carrillo, E, Berrizbeitia, M, Guevara, L, Pernalete, N, Ontiveros, C, Zigrang, W, Blakney, E, Rosenblit, P, Weinstein, R, Klaff, L, Lipetz, R, Busick, E, Tung, P, Cooperman, M, Michael, S, Sun, Ch, Hart, T, Maddux, A, Bowden, R, East, C, Arakaki, R, Villafuerte, B, Mamish, Z, Mendez, R, Connery, L, Nour, K, Wynne, A, Busch, R, Zamora, B, Sachson, R, Prasad, J, Lasala, G, Smith, M, Fitz Patrick, D, Ruiz Rivera, L, Barranco, E, Solomon, R, Woolley, A, Brown, C, Freedman, Z, Schmidt, S, Pollock, J, Ruddy, M, Kopyt, Np, Bazzi, A, Horowitz, B, Feng, W, Wahl, T, Duprez, D, Gilbert, J, Steigerwalt, S, Jacqmein, J, Gorton, S, 3rd, Allison J., Pino, J, Lock, J, Leimbach, W, Anderson, J, Beacom, M, Craig, W, Gorson, D, Kerstein, H, Segal, S, Downey, H, Ledger, G, Mcgill, J, Gabriel, J, Nolen, T, Levinson, L, Williams, T, Levenson, D, Lerman, S, Minehart, C, Agarwal, N, Verma, S, Valitutto, M, Demetry, K, Mersey, J, Koeper, D, Fanti, P, Eng, G, Grimm, R, Fagan, T, Bajaj, M, Katz, L, Portnay, G, Altschuller, A, Desai, V, Bilazarian, S, Ipp, E, Rodelas, R, Burstein, D, Berg, J, Velez, J, Lund, R, Rekhi, A, Martin, E, Robertson, D, Singh, N, Narayan, P, Moustafa, M, Lanier, D, Seidner, M, Phillips, A, Vaughters, B, Sprague, A, Swartz, S, Lopez, R, Kumar, J, Bressler, P, Sadler, L, Wise, J, Kilbane, A., and Groningen Kidney Center (GKC)

Subjects
Male, Hyperkalemia, CARDIOVASCULAR MORTALITY, BLOOD-PRESSURE, Angiotensin-Converting Enzyme Inhibitors, Type 2 diabetes, GLOMERULAR-FILTRATION-RATE, DOUBLE-BLIND, chemistry.chemical_compound, Fumarates, cardiovascular disease, Renin, Treatment Failure, Settore MED/49 - Scienze Tecniche Dietetiche Applicate, 610 Medicine & health, diabetes, Medicine (all), Hazard ratio, aliskiren, diabete, trial clinico, Liter, General Medicine, Middle Aged, hypertension, Cardiovascular Diseases, Combination, HEART-FAILURE, Drug Therapy, Combination, Female, Kidney Diseases, type 2 diabetes, medicine.symptom, Type 2, medicine.medical_specialty, Patient Dropouts, Urology, Hypokalemia, Aliskiren, chronic kidney disease, Placebo, Angiotensin Receptor Antagonists, LEFT-VENTRICULAR DYSFUNCTION, Drug Therapy, Double-Blind Method, Diabetes Mellitus, medicine, Humans, CONVERTING-ENZYME INHIBITORS, Antihypertensive Agents, Aged, Amides, Diabetes Mellitus, Type 2, Follow-Up Studies, business.industry, medicine.disease, Confidence interval, Surgery, Blood pressure, MYOCARDIAL-INFARCTION, chemistry, SYSTOLIC DYSFUNCTION, FOLLOW-UP, business
Abstract

BACKGROUND This study was undertaken to determine whether use of the direct renin inhibitor aliskiren would reduce cardiovascular and renal events in patients with type 2 diabetes and chronic kidney disease, cardiovascular disease, or both. METHODS In a double-blind fashion, we randomly assigned 8561 patients to aliskiren (300 mg daily) or placebo as an adjunct to an angiotensin-converting-enzyme inhibitor or an angiotensin-receptor blocker. The primary end point was a composite of the time to cardiovascular death or a first occurrence of cardiac arrest with resuscitation; nonfatal myocardial infarction; nonfatal stroke; unplanned hospitalization for heart failure; end-stage renal disease, death attributable to kidney failure, or the need for renal-replacement therapy with no dialysis or transplantation available or initiated; or doubling of the baseline serum creatinine level. RESULTS The trial was stopped prematurely after the second interim efficacy analysis. After a median follow-up of 32.9 months, the primary end point had occurred in 783 patients (18.3%) assigned to aliskiren as compared with 732 (17.1%) assigned to placebo (hazard ratio, 1.08; 95% confidence interval [CI], 0.98 to 1.20; P = 0.12). Effects on secondary renal end points were similar. Systolic and diastolic blood pressures were lower with aliskiren (between-group differences, 1.3 and 0.6 mm Hg, respectively) and the mean reduction in the urinary albumin-to-creatinine ratio was greater (between-group difference, 14 percentage points; 95% CI, 11 to 17). The proportion of patients with hyperkalemia (serum potassium level, = 6 mmol per liter) was significantly higher in the aliskiren group than in the placebo group (11.2% vs. 7.2%), as was the proportion with reported hypotension (12.1% vs. 8.3%) (P CONCLUSIONS The addition of aliskiren to standard therapy with renin-angiotensin system blockade in patients with type 2 diabetes who are at high risk for cardiovascular and renal events is not supported by these data and may even be harmful. (Funded by Novartis; ALTITUDE ClinicalTrials.gov number, NCT00549757.)

Published
2012
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4. Masses classification using fuzzy active contours and fuzzy decision trees

Author

Gero L. Peters, Isabelle Bloch, Giovanni Palma, and Serge Muller

Subjects
Set (abstract data type), Active contour model, Fuzzy classification, business.industry, Decision tree, Segmentation, Pattern recognition, Artificial intelligence, business, Class (biology), Fuzzy logic, Energy (signal processing), Mathematics
Abstract

In this paper we propose a method to classify masses in digital breast tomosynthesis (DBT) datasets. First, markers of potential lesions are extracted and matched over the different projections. Then two level-set models are applied on each finding corresponding to spiculated and circumscribed mass assumptions respectively. The formulation of the active contours within this framework leads to several candidate contours for each finding. In addition, a membership value to the class contour is derived from the energy of the segmentation model, and allows associating several fuzzy contours from different projections to each set of markers corresponding to a lesion. Fuzzy attributes are computed for each fuzzy contour. Then the attributes corresponding to fuzzy contours associated to each set of markers are aggregated. Finally, these cumulated fuzzy attributes are processed by two distinct fuzzy decision trees in order to validate/invalidate the spiculated or circumscribed mass assumptions. The classification has been validated on a database of 23 real lesions using the leave-one-out method. An error classification rate of 9% was obtained with these data, which confirms the interest of the proposed approach.

Published
2008
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5. Wavelets and Fuzzy Contours in 3D-CAD for Digital Breast Tomosynthesis

Author

Sylvain Bernard, Isabelle Bloch, Serge Muller, and Gero L. Peters

Subjects
Digital mammography, business.industry, Fuzzy set, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Reconstruction algorithm, Filter (signal processing), Thresholding, Fuzzy logic, Wavelet, Computer vision, Artificial intelligence, business, Membership function, Mathematics
Abstract

Summary In this chapter we present a novel approach for the detection of different kinds of lesions in Digital Breast Tomosynthesis datasets. It consists in working directly on the projected views, providing the advantage of a reduced data volume to process, while staying independent of any given reconstruction algorithm, not yet fully optimized for this emerging modality. Our aim was to develop a single processing framework for the detection of different kinds of breast lesions. Introducing fuzzy processing enables us to maintain the evidence, and the strength of the evidence, gathered from each DBT projection image for each potential finding without making hard decisions in isolation. First, the projected views are filtered using different banks of multiscale wavelet filters allowing to better fit the wavelet to the pattern that may vary in a defined range of sizes. The different filter responses are then thresholded and the result is combined to obtain microcalcification and mass candidates. For each candidate, we create a fuzzy contour through a multi-level thresholding process. We extract attributes for each candidate contour that are characteristic for the different kinds of lesions to be detected. Fuzzy set definitions for the classes of the respective lesions are introduced that allow for the computation of fuzzy membership values for each candidate contour. Then, an aggregation operator is presented that combines information over the complete set of projected views, resulting in 3D fuzzy particles. A final decision is made taking into account information acquired over different successive processing steps. Visual examples of detection results are presented, along with a preliminary quantitative evaluation of the algorithm.

Published
2007
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6. Fast microcalcification detection on digital breast tomosynthesis datasets

Author

Razvan Iordache, Sylvain Bernard, Serge Muller, and Gero L. Peters

Subjects
medicine.diagnostic_test, business.industry, Computation, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Image segmentation, Thresholding, Tomosynthesis, Contrast-to-noise ratio, medicine, Mammography, Computer vision, Microcalcification, Artificial intelligence, Noise (video), medicine.symptom, business, Mathematics
Abstract

In this paper, we present a fast method for microcalcification detection in Digital Breast Tomosynthesis. Instead of applying the straight-forward reconstruction/filtering/thresholding approach, the filtering is performed on projections before simple back-projection reconstruction. This leads to a reduced computation time since the number of projections is generally much smaller than the number of slices. For an average breast thickness and a typical number of projections, the number of operations is reduced by a factor in the range of 2 to 4. At the same time, the approach yields a negligible decrease of the contrast to noise ratio in the reconstructed slices. Image segmentation results are presented and compared to the previous method as visual performance assessment.

Published
2007
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7. A hybrid active contour model for mass detection in digital breast tomosynthesis

Author

Sylvain Bernard, Serge Muller, Gero L. Peters, Bénédicte Grosjean, and Isabelle Bloch

Subjects
Active contour model, business.industry, Computer science, Feature vector, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Initialization, Image segmentation, Tomosynthesis, Wavelet, Computer-aided diagnosis, Segmentation, Computer vision, Artificial intelligence, business
Abstract

In this paper we present a novel approach for mass contour detection for 3D computer-aided detection (CAD) in digital breast tomosynthesis (DBT) data-sets. A hybrid active contour model, working directly on the projected views, is proposed. The responses of a wavelet filter applied on the projections are thresholded and combined to obtain markers for mass candidates. The contours of markers are extracted and serve as initialization for the active contour model, which is then used to extract mass contours in DBT projection images. A hybrid model is presented, taking into account several image-based external forces and implemented using a level-set formulation. A feature vector is computed from the detected contour, which may serve as input to a dedicated classifier. The segmentation method is applied to simulated images and to clinical cases. Image segmentation results are presented and compared to two standard active contour models. Evaluation of the performance on clinical data is obtained by comparison to manual segmentation by an expert. Performance on simulated images and visual performance assessment provide further illustration of the performance of the presented approach.

Published
2007
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8. Reconstruction-independent 3D CAD for mass detection in digital breast tomosynthesis using fuzzy particles

Author

Serge Muller, Sylvain Bernard, Gero L. Peters, Razvan Iordache, and Isabelle Bloch

Subjects
Set (abstract data type), Wavelet, Computer-aided diagnosis, business.industry, Fuzzy set, Computer vision, Sensitivity (control systems), Artificial intelligence, business, Thresholding, Fuzzy logic, Tomosynthesis, Mathematics
Abstract

In this paper we present a novel approach for mass detection in Digital Breast Tomosynthesis (DBT) datasets. A reconstruction-independent approach, working directly on the projected views, is proposed. Wavelet filter responses on the projections are thresholded and combined to obtain candidate masses. For each candidate, we create a fuzzy contour through a multi-level thresholding process. We introduce a fuzzy set definition for the class mass contour that allows the computation of fuzzy membership values for each candidate contour. Then, an aggregation operator is presented that combines information over the complete set of projected views, resulting in 3D fuzzy particles. A final decision is made taking into account all available information. The performance of the presented algorithm was evaluated on a database of 11 one-breast-cases resulting in a sensitivity (Se) of 0.86 and a false positive rate (FPR) of 3.5 per case.

Published
2006
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9. Micro-calcification detection in digital tomosynthesis mammography

Author

Frederick Wilson Wheeler, John Patrick Kaufhold, Serge Muller, A. G. Amitha Perera, Gero L. Peters, and Bernhard Erich Hermann Claus

Subjects
medicine.diagnostic_test, Pixel, business.industry, 3D reconstruction, medicine.disease, Digital Tomosynthesis Mammography, Computer-aided diagnosis, medicine, Mammography, Computer vision, Microcalcification, Artificial intelligence, medicine.symptom, Projection (set theory), business, Mathematics, Calcification
Abstract

A novel technique for the detection and enhancement of microcalcifications in digital tomosynthesis mammography (DTM) is presented. In this method, the DTM projection images are used directly, instead of using a 3D reconstruction. Calcification residual images are computed for each of the projection images. Calcification detection is then performed over 3D space, based on the values of the calcification residual images at projection points for each 3D point under test. The quantum, electronic, and tissue noise variance at each pixel in each of the calcification residuals is incorporated into the detection algorithm. The 3D calcification detection algorithm finds a minimum variance estimate of calcification attenuation present in 3D space based on the signal and variance of the calcification residual images at the corresponding points in the projection images. The method effectively detects calcifications in 3D in a way that both ameliorates the difficulties of joint tissue/microcalcification tomosynthetic reconstruction (streak artifacts, etc.) and exploits the well understood image properties of microcalcifications as they appear in 2D mammograms. In this method, 3D reconstruction and calcification detection and enhancement are effectively combined to create a calcification detection specific reconstruction. Motivation and details of the technique and statistical results for DTM data are provided.

Published
2006
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10. Reconstruction-Independent 3D CAD for Calcification Detection in Digital Breast Tomosynthesis Using Fuzzy Particles

Author

Gero L. Peters, Frederick Wilson Wheeler, Serge Muller, Sylvain Bernard, Razvan Iordache, and Isabelle Bloch

Subjects
Digital mammography, Computer science, business.industry, Mammary gland, Fuzzy set, Image processing, Digital Breast Tomosynthesis, Filter (signal processing), Iterative reconstruction, medicine.disease, Fuzzy logic, Thresholding, medicine.anatomical_structure, medicine, Computer vision, Microcalcification, Artificial intelligence, medicine.symptom, business, Calcification
Abstract

In this paper we present a novel approach for microcalcification detection in Digital Breast Tomosynthesis (DBT) datasets. A reconstruction-independent approach, working directly on the projected views, is proposed. Wavelet filter responses on the projections are thresholded and combined to obtain candidate microcalcifications. For each candidate, we create a fuzzy contour through a multi-level thresholding process. We introduce a fuzzy set definition for the class microcalcification contour that allows the computation of fuzzy membership values for each candidate contour. Then, an aggregation operator is presented that combines information over the complete set of projected views, resulting in 3D fuzzy particles. A final decision is made taking into account information acquired over a range of successive processing steps. A clinical example is provided that illustrates our approach. DBT still being a new modality, a similar published approach is not available for comparison and limited clinical data currently prevents a clinical evaluation of the algorithm. .

Published
2005
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