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1. Handbook of LHC Higgs Cross Sections: 4. Deciphering the Nature of the Higgs Sector

Author

de Florian, D., Grojean, C., Maltoni, F., Mariotti, C., Nikitenko, A., Pieri, M., Savard, P., Schumacher, M., Tanaka, R., Aggleton, R., Ahmad, M., Allanach, B., Anastasiou, C., Astill, W., Badger, S., Badziak, M., Baglio, J., Bagnaschi, E., Ballestrero, A., Banfi, A., Barducci, D., Beckingham, M., Becot, C., Bélanger, G., Bellm, J., Belyaev, N., Bernlochner, F. U., Beskidt, C., Biekötter, A., Bishara, F., Bizon, W., Bomark, N. E., Bonvini, M., Borowka, S., Bortolotto, V., Boselli, S., Botella, F. J., Boughezal, R., Branco, G. C., Brehmer, J., Brenner, L., Bressler, S., Brivio, I., Broggio, A., Brun, H., Buchalla, G., Burgard, C. D., Calandri, A., Caminada, L., Armadans, R. Caminal, Campanario, F., Campbell, J., Caola, F., Calame, C. M. Carloni, Carrazza, S., Carvalho, A., Casolino, M., Cata, O., Celis, A., Cerutti, F., Chanon, N., Chen, M., Chen, X., Nejad, B. Chokoufé, Christensen, N., Ciuchini, M., Contino, R., Corbett, T., Costa, R., Curtin, D., Dall'Osso, M., David, A., Dawson, S., de Blas, J., de Boer, W., Manzano, P. de Castro, Degrande, C., Delgado, R. L., Demartin, F., Denner, A., Di Micco, B., Di Nardo, R., Dittmaier, S., Dobado, A., Dorigo, T., Dreyer, F. A., Dührssen, M., Duhr, C., Dulat, F., Ecker, K., Ellis, K., Ellwanger, U., Englert, C., Espriu, D., Falkowski, A., Fayard, L., Feger, R., Ferrera, G., Ferroglia, A., Fidanza, N., Figy, T., Flechl, M., Fontes, D., Forte, S., Francavilla, P., Franco, E., Frederix, R., Freitas, A., Freitas, F. F., Frensch, F., Frixione, S., Fuks, B., Furlan, E., Gadatsch, S., Gao, J., Gao, Y., Garzelli, M. V., Gehrmann, T., Gerosa, R., Ghezzi, M., Ghosh, D., Gieseke, S., Gillberg, D., Giudice, G. F., Glover, E. W. N., Goertz, F., Gonçalves, D., Gonzalez-Fraile, J., Gorbahn, M., Gori, S., Gottardo, C. A., Gouzevitch, M., Govoni, P., Gray, D., Grazzini, M., Greiner, N., Greljo, A., Grigo, J., Gritsan, A. V., Gröber, R., Guindon, S., Haber, H. E., Han, C., Han, T., Harlander, R., Harrendorf, M. A., Hartanto, H. B., Hays, C., Heinemeyer, S., Heinrich, G., Herrero, M., Herzog, F., Hespel, B., Hirschi, V., Hoeche, S., Honeywell, S., Huber, S. J., Hugonie, C., Huston, J., Ilnicka, A., Isidori, G., Jäger, B., Jaquier, M., Jones, S. P., Juste, A., Kallweit, S., Kaluza, A., Kardos, A., Karlberg, A., Kassabov, Z., Kauer, N., Kazakov, D. I., Kerner, M., Kilian, W., Kling, F., Köneke, K., Kogler, R., Konoplich, R., Kortner, S., Kraml, S., Krause, C., Krauss, F., Krawczyk, M., Kulesza, A., Kuttimalai, S., Lane, R., Lazopoulos, A., Lee, G., Lenzi, P., Lewis, I. M., Li, Y., Liebler, S., Lindert, J., Liu, X., Liu, Z., Llanes-Estrada, F. J., Logan, H. E., Lopez-Val, D., Low, I., Luisoni, G., Maierhöfer, P., Maina, E., Mansoulié, B., Mantler, H., Mantoani, M., Marini, A. C., Outschoorn, V. I. Martinez, Marzani, S., Marzocca, D., Massironi, A., Mawatari, K., Mazzitelli, J., McCarn, A., Mellado, B., Melnikov, K., Menari, S. B., Merlo, L., Meyer, C., Milenovic, P., Mimasu, K., Mishima, S., Mistlberger, B., Moch, S. -O., Mohammadi, A., Monni, P. F., Montagna, G., Llácer, M. Moreno, Moretti, N., Moretti, S., Motyka, L., Mück, A., Mühlleitner, M., Munir, S., Musella, P., Nadolsky, P., Napoletano, D., Nebot, M., Neu, C., Neubert, M., Nevzorov, R., Nicrosini, O., Nielsen, J., Nikolopoulos, K., No, J. M., O'Brien, C., Ohl, T., Oleari, C., Orimoto, T., Pagani, D., Pandini, C. E., Papaefstathiou, A., Papanastasiou, A. S., Passarino, G., Pecjak, B. D., Pelliccioni, M., Perez, G., Perrozzi, L., Petriello, F., Petrucciani, G., Pianori, E., Piccinini, F., Pierini, M., Pilkington, A., Plätzer, S., Plehn, T., Podskubka, R., Potter, C. T., Pozzorini, S., Prokofiev, K., Pukhov, A., Puljak, I., Queitsch-Maitland, M., Quevillon, J., Rathlev, D., Rauch, M., Re, E., Rebelo, M. N., Rebuzzi, D., Reina, L., Reuschle, C., Reuter, J., Riembau, M., Riva, F., Rizzi, A., Robens, T., Röntsch, R., Rojo, J., Romão, J. C., Rompotis, N., Roskes, J., Roth, R., Salam, G. P., Salerno, R., Sampaio, M. O. P., Santos, R., Sanz, V., Sanz-Cillero, J. J., Sargsyan, H., Sarica, U., Schichtel, P., Schlenk, J., Schmidt, T., Schmitt, C., Schönherr, M., Schubert, U., Schulze, M., Sekula, S., Sekulla, M., Shabalina, E., Shao, H. S., Shelton, J., Shepherd-Themistocleous, C. H., Shim, S. Y., Siegert, F., Signer, A., Silva, J. P., Silvestrini, L., Sjodahl, M., Slavich, P., Slawinska, M., Soffi, L., Spannowsky, M., Speckner, C., Sperka, D. M., Spira, M., Stål, O., Staub, F., Stebel, T., Stefaniak, T., Steinhauser, M., Stewart, I. W., Strassler, M. J., Streicher, J., Strom, D. M., Su, S., Sun, X., Tackmann, F. J., Tackmann, K., Teixeira, A. M., de Lima, R. Teixeira, Theeuwes, V., Thorne, R., Tommasini, D., Torrielli, P., Tosi, M., Tramontano, F., Trócsányi, Z., Trott, M., Tsinikos, I., Ubiali, M., Vanlaer, P., Verkerke, W., Vicini, A., Viliani, L., Vryonidou, E., Wackeroth, D., Wagner, C. E. M., Wang, J., Wayand, S., Weiglein, G., Weiss, C., Wiesemann, M., Williams, C., Winter, J., Winterbottom, D., Wolf, R., Xiao, M., Yang, L. L., Yohay, R., Yuen, S. P. Y., Zanderighi, G., Zaro, M., Zeppenfeld, D., Ziegler, R., Zirke, T., and Zupan, J.

Subjects
High Energy Physics - Phenomenology, High Energy Physics - Experiment
Abstract

This Report summarizes the results of the activities of the LHC Higgs Cross Section Working Group in the period 2014-2016. The main goal of the working group was to present the state-of-the-art of Higgs physics at the LHC, integrating all new results that have appeared in the last few years. The first part compiles the most up-to-date predictions of Higgs boson production cross sections and decay branching ratios, parton distribution functions, and off-shell Higgs boson production and interference effects. The second part discusses the recent progress in Higgs effective field theory predictions, followed by the third part on pseudo-observables, simplified template cross section and fiducial cross section measurements, which give the baseline framework for Higgs boson property measurements. The fourth part deals with the beyond the Standard Model predictions of various benchmark scenarios of Minimal Supersymmetric Standard Model, extended scalar sector, Next-to-Minimal Supersymmetric Standard Model and exotic Higgs boson decays. This report follows three previous working-group reports: Handbook of LHC Higgs Cross Sections: 1. Inclusive Observables (CERN-2011-002), Handbook of LHC Higgs Cross Sections: 2. Differential Distributions (CERN-2012-002), and Handbook of LHC Higgs Cross Sections: 3. Higgs properties (CERN-2013-004). The current report serves as the baseline reference for Higgs physics in LHC Run 2 and beyond., Comment: 869 pages, 295 figures, 248 tables and 1645 citations. Working Group web page: https://twiki.cern.ch/twiki/bin/view/LHCPhysics/LHCHXSWG

Published
2016
Full Text
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4. CERN Yellow Reports: Monographs, Vol 2 (2017): Handbook of LHC Higgs cross sections: 4. Deciphering the nature of the Higgs sector

Author

de Florian, D., Grojean, C., Maltoni, F., Mariotti, C., Nikitenko, A., Pieri, M., Savard, P., Schumacher, M., Tanaka, R., Aggleton, R., Ahmad, M., Allanach, B., Anastasiou, C., Astill, W., Badger, S., Badziak, M., Baglio, J., Bagnaschi, E., Ballestrero, A., Banfi, A., Barducci, D., Beckingham, M., Becot, C., Bélanger, G., Bellm, J., Belyaev, N., Bernlochner, F. U., Beskidt, C., Biekötter, A., Bishara, F., Bizon, W., Bomark, N. E., Bonvini, M., Borowka, S., Bortolotto, V., Boselli, S., Botella, F. J., Boughezal, R., Branco, G. C., Brehmer, J., Brenner, L., Bressler, S., Brivio, I., Broggio, A., Brun, H., Buchalla, G., Burgard, C. D., Calandri, A., Caminada, L., Caminal Armadans, R., Campanario, F., Campbell, J., Caola, F., Carloni Calame, C. M., Carrazza, S., Carvalho, A., Casolino, M., Cata, O., Celis, A., Cerutti, F., Chanon, N., Chen, M., Chen, X., Chokoufé Nejad, B., Christensen, N., Ciuchini, M., Contino, R., Corbett, T., Costa, R., Curtin, D., Dall'Osso, M., David, A., Dawson, S., de Blas, J., de Boer, W., de Castro Manzano, P., Degrande, C., Delgado, R. L., Demartin, F., Denner, A., Di Micco, B., Di Nardo, R., Dittmaier, S., Dobado, A., Dorigo, T., Dreyer, F. A., Dührssen, M., Duhr, C., Dulat, F., Ecker, K., Ellis, K., Ellwanger, U., Englert, C., Espriu, D., Falkowski, A., Fayard, L., Feger, R., Ferrera, G., Ferroglia, A., Fidanza, N., Figy, T., Flechl, M., Fontes, D., Forte, S., Francavilla, P., Franco, E., Frederix, R., Freitas, A., Freitas, F. F., Frensch, F., Frixione, S., Fuks, B., Furlan, E., Gadatsch, S., Gao, J., Gao, Y., Garzelli, M. V., Gehrmann, T., Gerosa, R., Ghezzi, M., Ghosh, D., Gieseke, S., Gillberg, D., Giudice, G. F., Glover, E. W. N., Goertz, F., Gonçalves, D., Gonzalez-Fraile, J., Gorbahn, M., Gori, S., Gottardo, C. A., Gouzevitch, M., Govoni, P., Gray, D., Grazzini, M., Greiner, N., Greljo, A., Grigo, J., Gritsan, A. V., Gröber, R., Guindon, S., Haber, H. E., Han, C., Han, T., Harlander, R., Harrendorf, M. A., Hartanto, H. B., Hays, C., Heinemeyer, S., Heinrich, G., Herrero, M., Herzog, F., Hespel, B., Hirschi, V., Hoeche, S., Honeywell, S., Huber, S. J., Hugonie, C., Huston, J., Ilnicka, A., Isidori, G., Jäger, B., Jaquier, M., Jones, S. P., Juste, A., Kallweit, S., Kaluza, A., Kardos, A., Karlberg, A., Kassabov, Z., Kauer, N., Kazakov, D. I., Kerner, M., Kilian, W., Kling, F., Köneke, K., Kogler, R., Konoplich, R., Kortner, S., Kraml, S., Krause, C., Krauss, F., Krawczyk, M., Kulesza, A., Kuttimalai, S., Lane, R., Lazopoulos, A., Lee, G., Lenzi, P., Lewis, I. M., Li, Y., Liebler, S., Lindert, J., Liu, X., Liu, Z., Llanes-Estrada, F. J., Logan, H. E., Lopez-Val, D., Low, I., Luisoni, G., Maierhöfer, P., Maina, E., Mansoulié, B., Mantler, H., Mantoani, M., Marini, A. C., Martinez Outschoorn, V. I., Marzani, S., Marzocca, D., Massironi, A., Mawatari, K., Mazzitelli, J., McCarn, A., Mellado, B., Melnikov, K., Menari, S. B., Merlo, L., Meyer, C., Milenovic, P., Mimasu, K., Mishima, S., Mistlberger, B., Moch, S. -O., Mohammadi, A., Monni, P. F., Montagna, G., Moreno Llácer, M., Moretti, N., Moretti, S., Motyka, L., Mück, A., Mühlleitner, M., Munir, S., Musella, P., Nadolsky, P., Napoletano, D., Nebot, M., Neu, C., Neubert, M., Nevzorov, R., Nicrosini, O., Nielsen, J., Nikolopoulos, K., No, J. M., O'Brien, C., Ohl, T., Oleari, C., Orimoto, T., Pagani, D., Pandini, C. E., Papaefstathiou, A., Papanastasiou, A. S., Passarino, G., Pecjak, B. D., Pelliccioni, M., Perez, G., Perrozzi, L., Petriello, F., Petrucciani, G., Pianori, E., Piccinini, F., Pierini, M., Pilkington, A., Plätzer, S., Plehn, T., Podskubka, R., Potter, C. T., Pozzorini, S., Prokofiev, K., Pukhov, A., Puljak, I., Queitsch-Maitland, M., Quevillon, J., Rathlev, D., Rauch, M., Re, E., Rebelo, M. N., Rebuzzi, D., Reina, L., Reuschle, C., Reuter, J., Riembau, M., Riva, F., Rizzi, A., Robens, T., Röntsch, R., Rojo, J., Romão, J. C., Rompotis, N., Roskes, J., Roth, R., Salam, G. P., Salerno, R., Sampaio, M. O. P., Santos, R., Sanz, V., Sanz-Cillero, J. J., Sargsyan, H., Sarica, U., Schichtel, P., Schlenk, J., Schmidt, T., Schmitt, C., Schönherr, M., Schubert, U., Schulze, M., Sekula, S., Sekulla, M., Shabalina, E., Shao, H. S., Shelton, J., Shepherd-Themistocleous, C. H., Shim, S. Y., Siegert, F., Signer, A., Silva, J. P., Silvestrini, L., Sjodahl, M., Slavich, P., Slawinska, M., Soffi, L., Spannowsky, M., Speckner, C., Sperka, D. M., Spira, M., Stål, O., Staub, F., Stebel, T., Stefaniak, T., Steinhauser, M., Stewart, I. W., Strassler, M. J., Streicher, J., Strom, D. M., Su, S., Sun, X., Tackmann, F. J., Tackmann, K., Teixeira, A. M., Teixeira de Lima, R., Theeuwes, V., Thorne, R., Tommasini, D., Torrielli, P., Tosi, M., Tramontano, F., Trócsányi, Z., Trott, M., Tsinikos, I., Ubiali, M., Vanlaer, P., Verkerke, W., Vicini, A., Viliani, L., Vryonidou, E., Wackeroth, D., Wagner, C. E. M., Wang, J., Wayand, S., Weiglein, G., Weiss, C., Wiesemann, M., Williams, C., Winter, J., Winterbottom, D., Wolf, R., Xiao, M., Yang, L. L., Yohay, R., Yuen, S. P. Y., Zanderighi, G., Zaro, M., Zeppenfeld, D., Ziegler, R., Zirke, T., Zupan, J., D. de Florian, C. Grojean, F. Maltoni, C. Mariotti, A. Nikitenko, M. Pieri, P. Savard, M. Schumacher, R. Tanaka, de Florian, D., Grojean, C., Maltoni, F., Mariotti, C., Nikitenko, A., Pieri, M., Savard, P., Schumacher, M., Tanaka, R., Aggleton, R., Ahmad, M., Allanach, B., Anastasiou, C., Astill, W., Badger, S., Badziak, M., Baglio, J., Bagnaschi, E., Ballestrero, A., Banfi, A., Barducci, D., Beckingham, M., Becot, C., Bélanger, G., Bellm, J., Belyaev, N., Bernlochner, F. U., Beskidt, C., Biekötter, A., Bishara, F., Bizon, W., Bomark, N. E., Bonvini, M., Borowka, S., Bortolotto, V., Boselli, S., Botella, F. J., Boughezal, R., Branco, G. C., Brehmer, J., Brenner, L., Bressler, S., Brivio, I., Broggio, A., Brun, H., Buchalla, G., Burgard, C. D., Calandri, A., Caminada, L., Caminal Armadans, R., Campanario, F., Campbell, J., Caola, F., Carloni Calame, C. M., Carrazza, S., Carvalho, A., Casolino, M., Cata, O., Celis, A., Cerutti, F., Chanon, N., Chen, M., Chen, X., Chokoufé Nejad, B., Christensen, N., Ciuchini, M., Contino, R., Corbett, T., Costa, R., Curtin, D., Dall'Osso, M., David, A., Dawson, S., de Blas, J., de Boer, W., de Castro Manzano, P., Degrande, C., Delgado, R. L., Demartin, F., Denner, A., Di Micco, B., Di Nardo, R., Dittmaier, S., Dobado, A., Dorigo, T., Dreyer, F. A., Dührssen, M., Duhr, C., Dulat, F., Ecker, K., Ellis, K., Ellwanger, U., Englert, C., Espriu, D., Falkowski, A., Fayard, L., Feger, R., Ferrera, G., Ferroglia, A., Fidanza, N., Figy, T., Flechl, M., Fontes, D., Forte, S., Francavilla, P., Franco, E., Frederix, R., Freitas, A., Freitas, F. F., Frensch, F., Frixione, S., Fuks, B., Furlan, E., Gadatsch, S., Gao, J., Gao, Y., Garzelli, M. V., Gehrmann, T., Gerosa, R., Ghezzi, M., Ghosh, D., Gieseke, S., Gillberg, D., Giudice, G. F., Glover, E. W. N., Goertz, F., Gonçalves, D., Gonzalez-Fraile, J., Gorbahn, M., Gori, S., Gottardo, C. A., Gouzevitch, M., Govoni, P., Gray, D., Grazzini, M., Greiner, N., Greljo, A., Grigo, J., Gritsan, A. V., Gröber, R., Guindon, S., Haber, H. E., Han, C., Han, T., Harlander, R., Harrendorf, M. A., Hartanto, H. B., Hays, C., Heinemeyer, S., Heinrich, G., Herrero, M., Herzog, F., Hespel, B., Hirschi, V., Hoeche, S., Honeywell, S., Huber, S. J., Hugonie, C., Huston, J., Ilnicka, A., Isidori, G., Jäger, B., Jaquier, M., Jones, S. P., Juste, A., Kallweit, S., Kaluza, A., Kardos, A., Karlberg, A., Kassabov, Z., Kauer, N., Kazakov, D. I., Kerner, M., Kilian, W., Kling, F., Köneke, K., Kogler, R., Konoplich, R., Kortner, S., Kraml, S., Krause, C., Krauss, F., Krawczyk, M., Kulesza, A., Kuttimalai, S., Lane, R., Lazopoulos, A., Lee, G., Lenzi, P., Lewis, I. M., Li, Y., Liebler, S., Lindert, J., Liu, X., Liu, Z., Llanes-Estrada, F. J., Logan, H. E., Lopez-Val, D., Low, I., Luisoni, G., Maierhöfer, P., Maina, E., Mansoulié, B., Mantler, H., Mantoani, M., Marini, A. C., Martinez Outschoorn, V. I., Marzani, S., Marzocca, D., Massironi, A., Mawatari, K., Mazzitelli, J., McCarn, A., Mellado, B., Melnikov, K., Menari, S. B., Merlo, L., Meyer, C., Milenovic, P., Mimasu, K., Mishima, S., Mistlberger, B., Moch, S.-O., Mohammadi, A., Monni, P. F., Montagna, G., Moreno Llácer, M., Moretti, N., Moretti, S., Motyka, L., Mück, A., Mühlleitner, M., Munir, S., Musella, P., Nadolsky, P., Napoletano, D., Nebot, M., Neu, C., Neubert, M., Nevzorov, R., Nicrosini, O., Nielsen, J., Nikolopoulos, K., No, J. M., O'Brien, C., Ohl, T., Oleari, C., Orimoto, T., Pagani, D., Pandini, C. E., Papaefstathiou, A., Papanastasiou, A. S., Passarino, G., Pecjak, B. D., Pelliccioni, M., Perez, G., Perrozzi, L., Petriello, F., Petrucciani, G., Pianori, E., Piccinini, F., Pierini, M., Pilkington, A., Plätzer, S., Plehn, T., Podskubka, R., Potter, C. T., Pozzorini, S., Prokofiev, K., Pukhov, A., Puljak, I., Queitsch-Maitland, M., Quevillon, J., Rathlev, D., Rauch, M., Re, E., Rebelo, M. N., Rebuzzi, D., Reina, L., Reuschle, C., Reuter, J., Riembau, M., Riva, F., Rizzi, A., Robens, T., Röntsch, R., Rojo, J., Romão, J. C., Rompotis, N., Roskes, J., Roth, R., Salam, G. P., Salerno, R., Sampaio, M. O. P., Santos, R., Sanz, V., Sanz-Cillero, J. J., Sargsyan, H., Sarica, U., Schichtel, P., Schlenk, J., Schmidt, T., Schmitt, C., Schönherr, M., Schubert, U., Schulze, M., Sekula, S., Sekulla, M., Shabalina, E., Shao, H. S., Shelton, J., Shepherd-Themistocleous, C. H., Shim, S. Y., Siegert, F., Signer, A., Silva, J. P., Silvestrini, L., Sjodahl, M., Slavich, P., Slawinska, M., Soffi, L., Spannowsky, M., Speckner, C., Sperka, D. M., Spira, M., Stål, O., Staub, F., Stebel, T., Stefaniak, T., Steinhauser, M., Stewart, I. W., Strassler, M. J., Streicher, J., Strom, D. M., Su, S., Sun, X., Tackmann, F. J., Tackmann, K., Teixeira, A. M., Teixeira de Lima, R., Theeuwes, V., Thorne, R., Tommasini, D., Torrielli, P., Tosi, M., Tramontano, F., Trócsányi, Z., Trott, M., Tsinikos, I., Ubiali, M., Vanlaer, P., Verkerke, W., Vicini, A., Viliani, L., Vryonidou, E., Wackeroth, D., Wagner, C. E. M., Wang, J., Wayand, S., Weiglein, G., Weiss, C., Wiesemann, M., Williams, C., Winter, J., Winterbottom, D., Wolf, R., Xiao, M., Yang, L. L., Yohay, R., Yuen, S. P. Y., Zanderighi, G., Zaro, M., Zeppenfeld, D., Ziegler, R., Zirke, T., and Zupan, J.

Subjects
Higgs, CERN, LHC
Abstract

Edited by D. de Florian, C. Grojean, F. Maltoni, C. Mariotti, A. Nikitenko, M. Pieri, P. Savard, M. Schumacher, R. Tanaka CERN-2017-002-M, ISBN (Print) 978–92–9083–442–7, ISBN (PDF) 978–92–9083–443–4

Published
2017

5. Handbook of LHC Higgs Cross Sections: 4. Deciphering the Nature of the Higgs Sector

Author

de Florian, D., Grojean, C., Maltoni, F., Mariotti, C., Nikitenko, A., Pieri, M., Savard, P., Schumacher, M., R. Tanaka (eds. )., Aggleton, R., Ahmad, M., Allanach, B., Anastasiou, C., Astill, W., Badger, S., Badziak, M., Baglio, J., Bagnaschi, E., Ballestrero, A., Banfi, A., Barducci, D., Beckingham, M., Becot, C., Bélanger, G., Bellm, J., Belyaev, N., Bernlochner, F. U., Beskidt, C., Biekötter, A., Bishara, F., Bizon, W., Bomark, N. E., Bonvini, M., Borowka, S., Bortolotto, V., Boselli, S., Botella, F. J., Boughezal, R., Branco, G. C., Brehmer, J., Brenner, L., Bressler, S., Brivio, I., Broggio, A., Brun, H., Buchalla, G., Burgard, C. D., Calandri, A., Caminada, L., Caminal Armadans, R., Campanario, F., Campbell, J., Caola, F., Carloni Calame, C. M., Carrazza, S., Carvalho, A., Casolino, M., Cata, O., Celis, A., Cerutti, F., Chanon, N., Chen, M., Chen, X., Chokoufé Nejad, B., Christensen, N., Ciuchini, M., Contino, R., Corbett, T., Costa, R., Curtin, D., Dall'Osso, M., David, A., Dawson, S., DE BLAS MATEO, Jorge, de Boer, W., de Castro Manzano, P., Degrande, C., Delgado, R. L., Demartin, F., Denner, A., Di Micco, B., DI NARDO DI MAIO, Raffaele, Dittmaier, S., Dobado, A., Dorigo, T., Dreyer, F. A., Dührssen, M., Duhr, C., Dulat, F., Ecker, K., Ellis, K., Ellwanger, U., Englert, C., Espriu, D., Falkowski, A., Fayard, L., Feger, R., Ferrera, G., Ferroglia, A., Fidanza, N., Figy, T., Flechl, M., Fontes, D., Forte, S., Francavilla, P., Franco, E., Frederix, R., Freitas, A., Freitas, F. F., Frensch, F., Frixione, S., Fuks, B., Furlan, E., Gadatsch, S., Gao, J., Gao, Y., Garzelli, M. V., Gehrmann, T., Gerosa, R., Ghezzi, M., Ghosh, D., Gieseke, S., Gillberg, D., Giudice, G. F., Glover, E. W. N., Goertz, F., Gonçalves, D., Gonzalez-Fraile, J., Gorbahn, M., Gori, S., Gottardo, C. A., Gouzevitch, M., Govoni, P., Gray, D., Grazzini, M., Greiner, N., Greljo, A., Grigo, J., Gritsan, A. V., Gröber, R., Guindon, S., Haber, H. E., Han, C., Han, T., Harlander, R., Harrendorf, M. A., Hartanto, H. B., Hays, C., Heinemeyer, S., Heinrich, G., Herrero, M., Herzog, F., Hespel, B., Hirschi, V., Hoeche, S., Honeywell, S., Huber, S. J., Hugonie, C., Huston, J., Ilnicka, A., Isidori, Gino, Jäger, B., Jaquier, M., Jones, S. P., Juste, A., Kallweit, S., Kaluza, A., Kardos, A., Karlberg, A., Kassabov, Z., Kauer, N., Kazakov, D. I., Kerner, M., Kilian, W., Kling, F., Köneke, K., Kogler, R., Konoplich, R., Kortner, S., Kraml, S., Krause, C., Krauss, F., Krawczyk, M., Kulesza, A., Kuttimalai, S., Lane, R., Lazopoulos, A., Lee, G., Lenzi, P., Lewis, I. M., Li, Y., Liebler, S., Lindert, J., Liu, X., Liu, Z., Llanes-Estrada, F. J., Logan, H. E., Lopez-Val, D., Low, I., Luisoni, G., Maierhöfer, P., Maina, E., Mansoulié, B., Mantler, H., Mantoani, M., Marini, A. C., Martinez Outschoorn, V. I., Marzani, S., Marzocca, D., Massironi, A., Mawatari, K., Mazzitelli, J., Mccarn, A., Mellado, B., Melnikov, K., Menari, S. B., Merlo, L., Meyer, C., Milenovic, P., Mimasu, K., Mishima, S., Mistlberger, B., Moch, S. -O., Mohammadi, A., Monni, P. F., Montagna, G., Moreno Llácer, M., Moretti, N., Moretti, S., Motyka, L., Mück, A., Mühlleitner, M., Munir, S., Musella, P., Nadolsky, P., Napoletano, D., Nebot, M., Neu, C., Neubert, M., Nevzorov, R., Nicrosini, O., Nielsen, J., Nikolopoulos, K., J. M., No, O'Brien, C., Ohl, T., Oleari, C., Orimoto, T., Pagani, D., Pandini, C. E., Papaefstathiou, A., Papanastasiou, A. S., Passarino, G., Pecjak, B. D., Pelliccioni, M., Perez, G., Perrozzi, L., Petriello, F., Petrucciani, G., Pianori, E., Piccinini, F., Pierini, M., Pilkington, A., Plätzer, S., Plehn, T., Podskubka, R., Potter, C. T., Pozzorini, S., Prokofiev, K., Pukhov, A., Puljak, I., Queitsch-Maitland, M., Quevillon, J., Rathlev, D., Rauch, M., Re, E., Rebelo, M. N., Rebuzzi, D., Reina, L., Reuschle, C., Reuter, J., Riembau, M., Riva, F., Rizzi, A., Robens, T., Röntsch, R., Rojo, J., Romão, J. C., Rompotis, N., Roskes, J., Roth, R., Salam, G. P., Salerno, R., Sampaio, M. O. P., Santos, R., Sanz, V., Sanz-Cillero, J. J., Sargsyan, H., Sarica, U., Schichtel, P., Schlenk, J., Schmidt, T., Schmitt, C., Schönherr, M., Schubert, U., Schulze, M., Sekula, S., Sekulla, M., Shabalina, E., Shao, H. S., Shelton, J., Shepherd-Themistocleous, C. H., Shim, S. Y., Siegert, F., Signer, A., Silva, J. P., Silvestrini, L., Sjodahl, M., Slavich, P., Slawinska, M., Soffi, L., Spannowsky, M., Speckner, C., Sperka, D. M., Spira, M., Stål, O., Staub, F., Stebel, T., Stefaniak, T., Steinhauser, M., Stewart, I. W., Strassler, M. J., Streicher, J., Strom, D. M., Su, S., Sun, X., Tackmann, F. J., Tackmann, K., Teixeira, A. M., Teixeira de Lima, R., Theeuwes, V., Thorne, R., Tommasini, Damiano, Torrielli, P., Tosi, M., Tramontano, F., Trócsányi, Z., Trott, M., Tsinikos, I., Ubiali, M., Vanlaer, P., Verkerke, W., Vicini, A., Viliani, L., Vryonidou, E., Wackeroth, D., Wagner, C. E. M., Wang, J., Wayand, S., Weiglein, G., Weiss, C., Wiesemann, M., Williams, C., Winter, J., Winterbottom, D., Wolf, R., Xiao, M., Yang, LIUYANG LILY, Yohay, R., Yuen, S. P. Y., Zanderighi, G., Zaro, M., Zeppenfeld, D., Ziegler, ROBERT Andreas, Zirke, T., and Zupan (The LHC Higgs Cross Section Working Group), J.

Published
2017

6. VBF and VH (Chapter I.5)

Author

Aggleton, R, Ahmad, M, Allanach, B, Anastasiou, C, Astill, W, Badger, S, Badziak, M, Baglio, J, Bagnaschi, E, Ballestrero, A, Banfi, A, Barducci, D, Beckingham, M, Becot, C, Bélanger, G, Bellm, J, Belyaev, N, Bernlochner, F, Beskidt, C, Biekötter, A, Bishara, F, Bizon, W, Bomark, N, Bonvini, M, Borowka, S, Bortolotto, V, Boselli, S, Botella, F, Boughezal, R, Branco, G, Brehmer, J, Brenner, L, Bressler, S, Brivio, I, Broggio, A, Brun, H, Buchalla, G, Burgard, C, Calandri, A, Caminada, L, Caminal Armadans, R, Campanario, F, Campbell, J, Caola, F, Carloni Calame, C, Carrazza, S, Carvalho, A, Casolino, M, Cata, O, Celis, A, Cerutti, F, Chanon, N, Chen, M, Chen, X, Chokoufé Nejad, B, Christensen, N, Ciuchini, M, Contino, R, Corbett, T, Costa, R, Curtin, D, Dall'Osso, M, David, A, Dawson, S, de Blas, J, de Boer, W, de Castro Manzano, P, Degrande, C, Delgado, R, Demartin, F, Denner, A, Di Micco, B, Di Nardo, R, Dittmaier, S, Dobado, A, Dorigo, T, Dreyer, F, Dührssen, M, Duhr, C, Dulat, F, Ecker, K, Ellis, K, Ellwanger, U, Englert, C, Espriu, D, Falkowski, A, Fayard, L, Feger, R, Ferrera, G, Ferroglia, A, Fidanza, N, Figy, T, Flechl, M, Fontes, D, Forte, S, Francavilla, P, Franco, E, Frederix, R, Freitas, A, Freitas, F, Frensch, F, Frixione, S, Fuks, B, Furlan, E, Gadatsch, S, Gao, J, Gao, Y, Garzelli, M, Gehrmann, T, Gerosa, R, Ghezzi, M, Ghosh, D, Gieseke, S, Gillberg, D, Giudice, G, Glover, E, Goertz, F, Gonçalves, D, Gonzalez-Fraile, J, Gorbahn, M, Gori, S, Gottardo, C, Gouzevitch, M, Govoni, P, Gray, D, Grazzini, M, Greiner, N, Greljo, A, Grigo, J, Gritsan, A, Gröber, R, Guindon, S, Haber, H, Han, C, Han, T, Harlander, R, Harrendorf, M, Hartanto, H, Hays, C, Heinemeyer, S, Heinrich, G, Herrero, M, Herzog, F, Hespel, B, Hirschi, V, Hoeche, S, Honeywell, S, Huber, S, Hugonie, C, Huston, J, Ilnicka, A, Isidori, G, Jäger, B, Jaquier, M, Jones, S, Juste, A, Kallweit, S, Kaluza, A, Kardos, A, Karlberg, A, Kassabov, Z, Kauer, N, Kazakov, D, Kerner, M, Kilian, W, Kling, F, Köneke, K, Kogler, R, Konoplich, R, Kortner, S, Kraml, S, Krause, C, Krauss, F, Krawczyk, M, Kulesza, A, Kuttimalai, S, Lane, R, Lazopoulos, A, Lee, G, Lenzi, P, Lewis, I, Li, Y, Liebler, S, Lindert, J, Liu, X, Liu, Z, Llanes-Estrada, F, Logan, H, Lopez-Val, D, Low, I, Luisoni, G, Maierhöfer, P, Maina, E, Mansoulié, B, Mantler, H, Mantoani, M, Marini, A, Martinez Outschoorn, V, Marzani, S, Marzocca, D, Massironi, A, Mawatari, K, Mazzitelli, J, Mccarn, A, Mellado, B, Melnikov, K, Menari, S, Merlo, L, Meyer, C, Milenovic, P, Mimasu, K, Mishima, S, Mistlberger, B, Moch, S, Mohammadi, A, Monni, P, Montagna, G, Moreno Llácer, M, Moretti, N, Moretti, S, Motyka, L, Mück, A, Mühlleitner, M, Munir, S, Musella, P, Nadolsky, P, Napoletano, D, Nebot, M, Neu, C, Neubert, M, Nevzorov, R, Nicrosini, O, Nielsen, J, Nikolopoulos, K, No, J, O'Brien, C, Ohl, T, Oleari, C, Orimoto, T, Pagani, D, Pandini, C, Papaefstathiou, A, Papanastasiou, A, Passarino, G, Pecjak, B, Pelliccioni, M, Perez, G, Perrozzi, L, Petriello, F, Petrucciani, G, Pianori, E, Piccinini, F, Pierini, M, Pilkington, A, Plätzer, S, Plehn, T, Podskubka, R, Potter, C, Pozzorini, S, Prokofiev, K, Pukhov, A, Puljak, I, Queitsch-Maitland, M, Quevillon, J, Rathlev, D, Rauch, M, Re, E, Rebelo, M, Rebuzzi, D, Reina, L, Reuschle, C, Reuter, J, Riembau, M, Riva, F, Rizzi, A, Robens, T, Röntsch, R, Rojo, J, Romão, J, Rompotis, N, Roskes, J, Roth, R, Salam, G, Salerno, R, Sampaio, M, Santos, R, Sanz, V, Sanz-Cillero, J, Sargsyan, H, Sarica, U, Schichtel, P, Schlenk, J, Schmidt, T, Schmitt, C, Schönherr, M, Schubert, U, Schulze, M, Sekula, S, Sekulla, M, Shabalina, E, Shao, H, Shelton, J, Shepherd-Themistocleous, C, Shim, S, Siegert, F, Signer, A, Silva, J, Silvestrini, L, Sjodahl, M, Slavich, P, Slawinska, M, Soffi, L, Spannowsky, M, Speckner, C, Sperka, D, Spira, M, Stål, O, Staub, F, Stebel, T, Stefaniak, T, Steinhauser, M, Stewart, I, Strassler, M, Streicher, J, Strom, D, Su, S, Sun, X, Tackmann, F, Tackmann, K, Teixeira, A, Teixeira de Lima, R, Theeuwes, V, Thorne, R, Tommasini, D, Torrielli, P, Tosi, M, Tramontano, F, Trócsányi, Z, Trott, M, Tsinikos, I, Ubiali, M, Vanlaer, P, Verkerke, W, Vicini, A, Viliani, L, Vryonidou, E, Wackeroth, D, Wagner, C, Wang, J, Wayand, S, Weiglein, G, Weiss, C, Wiesemann, M, Williams, C, Winter, J, Winterbottom, D, Wolf, R, Xiao, M, Yang, L, Yohay, R, Yuen, S, Zanderighi, G, Zaro, M, Zeppenfeld, D, Ziegler, R, Zirke, T, Zupan, J, de Florian, D, Grojean, C, Maltoni, F, Mariotti, C, Nikitenko, A, Pieri, M, Savard, P, Schumacher, M, Tanaka, R, Ellis, R, Sjödahl, M, Astill, WA, Dreyer, FA, Ellis, RK, Moch, S. O, OLEARI, CARLO, Pandini, CE, Salam, GP, Zirke, T., Aggleton, R, Ahmad, M, Allanach, B, Anastasiou, C, Astill, W, Badger, S, Badziak, M, Baglio, J, Bagnaschi, E, Ballestrero, A, Banfi, A, Barducci, D, Beckingham, M, Becot, C, Bélanger, G, Bellm, J, Belyaev, N, Bernlochner, F, Beskidt, C, Biekötter, A, Bishara, F, Bizon, W, Bomark, N, Bonvini, M, Borowka, S, Bortolotto, V, Boselli, S, Botella, F, Boughezal, R, Branco, G, Brehmer, J, Brenner, L, Bressler, S, Brivio, I, Broggio, A, Brun, H, Buchalla, G, Burgard, C, Calandri, A, Caminada, L, Caminal Armadans, R, Campanario, F, Campbell, J, Caola, F, Carloni Calame, C, Carrazza, S, Carvalho, A, Casolino, M, Cata, O, Celis, A, Cerutti, F, Chanon, N, Chen, M, Chen, X, Chokoufé Nejad, B, Christensen, N, Ciuchini, M, Contino, R, Corbett, T, Costa, R, Curtin, D, Dall'Osso, M, David, A, Dawson, S, de Blas, J, de Boer, W, de Castro Manzano, P, Degrande, C, Delgado, R, Demartin, F, Denner, A, Di Micco, B, Di Nardo, R, Dittmaier, S, Dobado, A, Dorigo, T, Dreyer, F, Dührssen, M, Duhr, C, Dulat, F, Ecker, K, Ellis, K, Ellwanger, U, Englert, C, Espriu, D, Falkowski, A, Fayard, L, Feger, R, Ferrera, G, Ferroglia, A, Fidanza, N, Figy, T, Flechl, M, Fontes, D, Forte, S, Francavilla, P, Franco, E, Frederix, R, Freitas, A, Freitas, F, Frensch, F, Frixione, S, Fuks, B, Furlan, E, Gadatsch, S, Gao, J, Gao, Y, Garzelli, M, Gehrmann, T, Gerosa, R, Ghezzi, M, Ghosh, D, Gieseke, S, Gillberg, D, Giudice, G, Glover, E, Goertz, F, Gonçalves, D, Gonzalez-Fraile, J, Gorbahn, M, Gori, S, Gottardo, C, Gouzevitch, M, Govoni, P, Gray, D, Grazzini, M, Greiner, N, Greljo, A, Grigo, J, Gritsan, A, Gröber, R, Guindon, S, Haber, H, Han, C, Han, T, Harlander, R, Harrendorf, M, Hartanto, H, Hays, C, Heinemeyer, S, Heinrich, G, Herrero, M, Herzog, F, Hespel, B, Hirschi, V, Hoeche, S, Honeywell, S, Huber, S, Hugonie, C, Huston, J, Ilnicka, A, Isidori, G, Jäger, B, Jaquier, M, Jones, S, Juste, A, Kallweit, S, Kaluza, A, Kardos, A, Karlberg, A, Kassabov, Z, Kauer, N, Kazakov, D, Kerner, M, Kilian, W, Kling, F, Köneke, K, Kogler, R, Konoplich, R, Kortner, S, Kraml, S, Krause, C, Krauss, F, Krawczyk, M, Kulesza, A, Kuttimalai, S, Lane, R, Lazopoulos, A, Lee, G, Lenzi, P, Lewis, I, Li, Y, Liebler, S, Lindert, J, Liu, X, Liu, Z, Llanes-Estrada, F, Logan, H, Lopez-Val, D, Low, I, Luisoni, G, Maierhöfer, P, Maina, E, Mansoulié, B, Mantler, H, Mantoani, M, Marini, A, Martinez Outschoorn, V, Marzani, S, Marzocca, D, Massironi, A, Mawatari, K, Mazzitelli, J, Mccarn, A, Mellado, B, Melnikov, K, Menari, S, Merlo, L, Meyer, C, Milenovic, P, Mimasu, K, Mishima, S, Mistlberger, B, Moch, S, Mohammadi, A, Monni, P, Montagna, G, Moreno Llácer, M, Moretti, N, Moretti, S, Motyka, L, Mück, A, Mühlleitner, M, Munir, S, Musella, P, Nadolsky, P, Napoletano, D, Nebot, M, Neu, C, Neubert, M, Nevzorov, R, Nicrosini, O, Nielsen, J, Nikolopoulos, K, No, J, O'Brien, C, Ohl, T, Oleari, C, Orimoto, T, Pagani, D, Pandini, C, Papaefstathiou, A, Papanastasiou, A, Passarino, G, Pecjak, B, Pelliccioni, M, Perez, G, Perrozzi, L, Petriello, F, Petrucciani, G, Pianori, E, Piccinini, F, Pierini, M, Pilkington, A, Plätzer, S, Plehn, T, Podskubka, R, Potter, C, Pozzorini, S, Prokofiev, K, Pukhov, A, Puljak, I, Queitsch-Maitland, M, Quevillon, J, Rathlev, D, Rauch, M, Re, E, Rebelo, M, Rebuzzi, D, Reina, L, Reuschle, C, Reuter, J, Riembau, M, Riva, F, Rizzi, A, Robens, T, Röntsch, R, Rojo, J, Romão, J, Rompotis, N, Roskes, J, Roth, R, Salam, G, Salerno, R, Sampaio, M, Santos, R, Sanz, V, Sanz-Cillero, J, Sargsyan, H, Sarica, U, Schichtel, P, Schlenk, J, Schmidt, T, Schmitt, C, Schönherr, M, Schubert, U, Schulze, M, Sekula, S, Sekulla, M, Shabalina, E, Shao, H, Shelton, J, Shepherd-Themistocleous, C, Shim, S, Siegert, F, Signer, A, Silva, J, Silvestrini, L, Sjodahl, M, Slavich, P, Slawinska, M, Soffi, L, Spannowsky, M, Speckner, C, Sperka, D, Spira, M, Stål, O, Staub, F, Stebel, T, Stefaniak, T, Steinhauser, M, Stewart, I, Strassler, M, Streicher, J, Strom, D, Su, S, Sun, X, Tackmann, F, Tackmann, K, Teixeira, A, Teixeira de Lima, R, Theeuwes, V, Thorne, R, Tommasini, D, Torrielli, P, Tosi, M, Tramontano, F, Trócsányi, Z, Trott, M, Tsinikos, I, Ubiali, M, Vanlaer, P, Verkerke, W, Vicini, A, Viliani, L, Vryonidou, E, Wackeroth, D, Wagner, C, Wang, J, Wayand, S, Weiglein, G, Weiss, C, Wiesemann, M, Williams, C, Winter, J, Winterbottom, D, Wolf, R, Xiao, M, Yang, L, Yohay, R, Yuen, S, Zanderighi, G, Zaro, M, Zeppenfeld, D, Ziegler, R, Zirke, T, Zupan, J, de Florian, D, Grojean, C, Maltoni, F, Mariotti, C, Nikitenko, A, Pieri, M, Savard, P, Schumacher, M, Tanaka, R, Ellis, R, Sjödahl, M, Astill, WA, Dreyer, FA, Ellis, RK, Moch, S. O, OLEARI, CARLO, Pandini, CE, Salam, GP, and Zirke, T.

Abstract

The production of a Standard Model Higgs boson in association with two hard jets in the forward and backward regions of the detector, frequently quoted as the “vector-boson fusion” (VBF) channel, and the production of a Higgs boson in association with a W or Z boson, known as “VH production” or “Higgsstrahlung”, represent cornerstones in a comprehensive study of Higgs boson couplings at the LHC. These production channels do not only provide valuable information on the couplings of Higgs bosons to the massive gauge bosons by themselves, but also allow for the isolation of the Higgs boson decays into -lepton or bottom-quark pairs, whose investigation is essential in the Higgs boson couplings analysis. In the previous reports [7–9], state-of-the-art predictions and error estimates for the total and differential cross sections for pp ! H + 2 jets and pp ! HV ! H + 2 leptons were compiled (with V = W; Z), but the process of improving and refining predictions is still ongoing, even within the Standard Model. In this contribution we update the cross-section predictions for VBF and VH production, covering integrated total and fiducial cross sections as well as differential distributions. In detail, the presented state-of-the-art predictions include QCD corrections up to next-to-next-to-leading order (NNLO), electroweak (EW) corrections up to next-to-leading order (NLO), and contributions from specific partonic channels that open at higher perturbative orders, such as photon-induced collisions or gluon-fusion contributions. Apart from collecting numerical results, we give recommendations as to how to combine the individual components and to assess conservative estimates of remaining theoretical uncertainties. Moreover, issues connected to the matching and the impact of parton showers (PS) are discussed.

Published
2017

7. Handbook of LHC Higgs Cross Sections: 4. Deciphering the Nature of the Higgs Sector

Author

Florian, D. de, Grojean, C., Maltoni, F., Mariotti, C., Nikitenko, A., Pieri, M., Savard, P., Schumacher, M., Tanaka, R., Aggleton, R., Ahmad, M.A., Allanach, B., Anastasiou, C., Astill, W., Badger, S.A., Badziak, M., Baglio, J., Bagnaschi, E., Ballestrero, A., Banfi, A., Barducci, D., Beckingham, M., Becot, C., Bélanger, G., Bellm, J., Belyaev, N., Bernlochner, F. U., Beskidt, C., Biekötter, A., Bishara, Fady, Bizon, W., Bomark, N. E., Bonvini, Marco, Borowka, S., Bortolotto, V., Boselli, S., Botella, F. J., Boughezal, R., Branco, G. C., Brehmer, J., Brenner, L., Bressler, S., Brivio, I., Broggio, A., Brun, V.H., Buchalla, G., Burgard, C. D., Calandri, A., Caminada, L., Armadans, R. Caminal, Campanario, F., Campbell, J., Caola, Fabrizio, Calame, C. M. Carloni, Carrazza, Stefano, Carvalho, A., Casolino, M., Cata, O., Celis, A., Cerutti, Francesco, Chanon, N., Chen, M., Chen, X., Nejad, B. Chokoufé, Christensen, N., Ciuchini, M., Contino, R., Corbett, T., Costa, S.R., Curtin, D.M., Dall'Osso, M., David, A., Dawson, S.J., Blas, J. de, Boer, W. de, Manzano, P. de Castro, Degrande, C., Rueda-Delgado, L.M., Demartin, Federico, Denner, A., Micco, B. Di, Nardo, R. Di, Dittmaier, S., Dobado, A., Dorigo, T., Dreyer, F. A., Dührssen, M., Duhr, C., Dulat, F., Ecker, K., Ellis, K.A., Ellwanger, U., Englert, C., Espriu, D., Falkowski, A., Fayard, L., Feger, R., Ferrera, G., Ferroglia, A., Fidanza, N., Figy, T., Flechl, M., Fontes, J.D., Forte, Stefano, Francavilla, P., Franco, E, Frederix, R., Freitas, A., Freitas, F., Frensch, F., Frixione, S., Fuks, B., Furlan, E., Gadatsch, S., Gao, J., Gao, Y., Garzelli, M. V., Gehrmann, T., Gerosa, R., Ghezzi, M., Ghosh, D., Gieseke, S., Gillberg, D., Giudice, G. F., Glover, E. W. N., Goertz, F., Gonçalves, D., Gonzalez-Fraile, J., Gorbahn, M., Gori, S., Gottardo, C. A., Gouzevitch, Maxime, Govoni, P., Gray, D., Grazzini, M., Greiner, N., Greljo, A., Grigo, J., Gritsan, A. V., Gröber, R., Guindon, S., Haber, H. E., Han, C., Han, T.S., Harlander, R., Harrendorf, M. A., Hartanto, H. B., Hays, C., Heinemeyer, S., Heinrich, G., Herrero, M., Herzog, F., Hespel, B., Hirschi, V., Hoeche, S., Honeywell, S., Huber, S. J., Hugonie, C., Huston, Joey, Ilnicka, A., Isidori, G., Jäger, B., Jaquier, M., Jones, S. P., Juste, A., Kallweit, S., Kaluza, A., Kardos, A., Karlberg, A.T., Kassabov, Zahari, Kauer, N., Kazakov, D. I., Kerner, M., Kilian, W., Kling, M.F., Köneke, K., Kogler, R., Konoplich, R., Kortner, S., Kraml, S., Krause, C., Krauss, F., Krawczyk, P.M., Kulesza, Anna, Kuttimalai, S., Lane, R., Lazopoulos, A., Lee, W.G., Lenzi, P., Lewis, I. M., Li, Y., Liebler, S., van Lindert, E.J., Liu, X., Liu, Z., Llanes-Estrada, F. J., Logan, H. E., Lopez-Val, D., Low, I., Luisoni, G., Maierhöfer, P., Maina, E., Mansoulié, B., Mantler, H., Mantoani, M., Marini, A. C., Outschoorn, V. I. Martinez, Marzani, Simone, Marzocca, D., Massironi, A., Mawatari, K., Mazzitelli, J., McCarn, A., Mellado, B., Melnikov, K., Menari, S. B., Merlo, L., Meyer, C., Milenovic, P., Mimasu, K., Mishima, S., Mistlberger, B., Moch, S. O., Mohammadi, A., Monni, P. F., Montagna, G., Llácer, M. Moreno, Moretti, N., Moretti, S., Motyka, L., Mück, A., Mühlleitner, M., Munir, S., Musella, P., Nadolsky, Pavel, Napoletano, D., Nebot, M., Neu, C., Neubert, R.E.M., Nevzorov, R., Nicrosini, O., Nielsen, J., Nikolopoulos, K., No, J. M., O'Brien, C., Ohl, T., Oleari, C., Orimoto, T. J., Pagani, D., Pandini, C. E., Papaefstathiou, A., Papanastasiou, A. S., Passarino, G., Pecjak, B. D., Pelliccioni, M., Perez, J.G., Perrozzi, Luca, Petriello, F., Petrucciani, G., Pianori, E., Piccinini, F., Pierini, M., Pilkington, A., Plätzer, S., Plehn, T., Podskubka, R., Potter, C. T., Pozzorini, S., Prokofiev, K., Pukhov, A., Puljak, I., Queitsch-Maitland, M., Quevillon, J., Rathlev, D., Rauch, S.A.M., Re, E., Rebelo, M. N., Rebuzzi, D., Reina, L., Reuschle, C., Reuter, J., Riembau, M., Riva, F., Rizzi, A., Robens, T., Röntsch, R., Rojo, J., Romão, J. C., Rompotis, N., Roskes, J., Roth, R., Salam, Gavin P., Salerno, R., Sampaio, M. O. P., Santos, R., Sanz-Nebot, V., Sanz-Cillero, J. J., Sargsyan, H., Sarica, U., Schichtel, P., Schlenk, J., Schmidt, T., Schmitt, C., Schönherr, M., Schubert, U., Schulze, M., Sekula, S. J., Sekulla, M., Shabalina, E., Shao, H. -S., Shelton, J., Shepherd-Themistocleous, C. H., Shim, S. Y., Siegert, F., Signer, A., Da Silva, J.P., Silvestrini, L., Sjodahl, M., Slavich, P., Slawinska, M., Soffi, L., Spannowsky, M., Speckner, C., Sperka, D. M., Spira, M., Stål, O., Staub, F., Stebel, T., Stefaniak, T., Steinhauser, M., Stewart, I. W., Strassler, M. J., Streicher, J., Strom, D. M., Su, S., Sun, X., Tackmann, F. J., Tackmann, K., Teixeira, A. M., Lima, R. Teixeira de, Theeuwes, V., Thorne, R., Tommasini, D., Torrielli, P., Tosi, M., Tramontano, F., Trócsányi, Z., Trott, M., Tsinikos, I., Ubiali, Maria, Vanlaer, P., Verkerke, W., Vicini, A., Viliani, L., Vryonidou, E., Wackeroth, D., Wagner, C. E. M., Wang, J., Wayand, S., Weiglein, G., Weiss, C., Wiesemann, M., Williams, C., Winter, J., Winterbottom, D., Wolf, R., Xiao, S.M., Yang, L. L., Yohay, R., Yuen, S. P. Y., Zanderighi, G., Zaro, M., Zeppenfeld, D., Ziegler, R., Zirke, T., Zupan, J., de Florian, Daniel, fabio, maltoni, Chiara, Mariotti, Nikitento, Aleksandr, Marco, Pieri, Pierre, Savard, and (Astro)-Particles Physics

Subjects
High Energy Physics - Phenomenology, High Energy Physics - Experiment (hep-ex), High Energy Physics - Phenomenology (hep-ph), hep-ex, High Energy Physics::Phenomenology, FOS: Physical sciences, hep-ph, High Energy Physics::Experiment, High Energy Physics - Experiment
Abstract

This Report summarizes the results of the activities of the LHC Higgs Cross Section Working Group in the period 2014-2016. The main goal of the working group was to present the state-of-the-art of Higgs physics at the LHC, integrating all new results that have appeared in the last few years. The first part compiles the most up-to-date predictions of Higgs boson production cross sections and decay branching ratios, parton distribution functions, and off-shell Higgs boson production and interference effects. The second part discusses the recent progress in Higgs effective field theory predictions, followed by the third part on pseudo-observables, simplified template cross section and fiducial cross section measurements, which give the baseline framework for Higgs boson property measurements. The fourth part deals with the beyond the Standard Model predictions of various benchmark scenarios of Minimal Supersymmetric Standard Model, extended scalar sector, Next-to-Minimal Supersymmetric Standard Model and exotic Higgs boson decays. This report follows three previous working-group reports: Handbook of LHC Higgs Cross Sections: 1. Inclusive Observables (CERN-2011-002), Handbook of LHC Higgs Cross Sections: 2. Differential Distributions (CERN-2012-002), and Handbook of LHC Higgs Cross Sections: 3. Higgs properties (CERN-2013-004). The current report serves as the baseline reference for Higgs physics in LHC Run 2 and beyond., Comment: 869 pages, 295 figures, 248 tables and 1645 citations. Working Group web page: https://twiki.cern.ch/twiki/bin/view/LHCPhysics/LHCHXSWG

Published
2016
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8. VBF and VH (Chapter I.5)

Author

Astill, WA, Bellm, J, Bizon, W, Campanario, F, Campbell, J, Denner, A, Dreyer, FA, Ellis, RK, Ferrera, G, Figy, T, Francavilla, P, Frederix, R, Frixione, S, Grazzini, M, Harlander, R, Hespel, B, Huston, J, Kallweit, S, Karlberg, A, Krauss, F, Kulesza, A, Luisoni, G, Moch, S. O, Mück, A, OLEARI, CARLO, Pandini, CE, Papaefstathiou, A, Plätzer, S, Re, E, Salam, GP, Schichtel, P, Sjödahl, M, Theeuwes, V, Torrielli, P, Vryonidou, E, Williams, C, Zanderighi, G, Zaro, M, Zirke, T., Aggleton, R, Ahmad, M, Allanach, B, Anastasiou, C, Astill, W, Badger, S, Badziak, M, Baglio, J, Bagnaschi, E, Ballestrero, A, Banfi, A, Barducci, D, Beckingham, M, Becot, C, Bélanger, G, Bellm, J, Belyaev, N, Bernlochner, F, Beskidt, C, Biekötter, A, Bishara, F, Bizon, W, Bomark, N, Bonvini, M, Borowka, S, Bortolotto, V, Boselli, S, Botella, F, Boughezal, R, Branco, G, Brehmer, J, Brenner, L, Bressler, S, Brivio, I, Broggio, A, Brun, H, Buchalla, G, Burgard, C, Calandri, A, Caminada, L, Caminal Armadans, R, Campanario, F, Campbell, J, Caola, F, Carloni Calame, C, Carrazza, S, Carvalho, A, Casolino, M, Cata, O, Celis, A, Cerutti, F, Chanon, N, Chen, M, Chen, X, Chokoufé Nejad, B, Christensen, N, Ciuchini, M, Contino, R, Corbett, T, Costa, R, Curtin, D, Dall'Osso, M, David, A, Dawson, S, de Blas, J, de Boer, W, de Castro Manzano, P, Degrande, C, Delgado, R, Demartin, F, Denner, A, Di Micco, B, Di Nardo, R, Dittmaier, S, Dobado, A, Dorigo, T, Dreyer, F, Dührssen, M, Duhr, C, Dulat, F, Ecker, K, Ellis, K, Ellwanger, U, Englert, C, Espriu, D, Falkowski, A, Fayard, L, Feger, R, Ferrera, G, Ferroglia, A, Fidanza, N, Figy, T, Flechl, M, Fontes, D, Forte, S, Francavilla, P, Franco, E, Frederix, R, Freitas, A, Freitas, F, Frensch, F, Frixione, S, Fuks, B, Furlan, E, Gadatsch, S, Gao, J, Gao, Y, Garzelli, M, Gehrmann, T, Gerosa, R, Ghezzi, M, Ghosh, D, Gieseke, S, Gillberg, D, Giudice, G, Glover, E, Goertz, F, Gonçalves, D, Gonzalez-Fraile, J, Gorbahn, M, Gori, S, Gottardo, C, Gouzevitch, M, Govoni, P, Gray, D, Grazzini, M, Greiner, N, Greljo, A, Grigo, J, Gritsan, A, Gröber, R, Guindon, S, Haber, H, Han, C, Han, T, Harlander, R, Harrendorf, M, Hartanto, H, Hays, C, Heinemeyer, S, Heinrich, G, Herrero, M, Herzog, F, Hespel, B, Hirschi, V, Hoeche, S, Honeywell, S, Huber, S, Hugonie, C, Huston, J, Ilnicka, A, Isidori, G, Jäger, B, Jaquier, M, Jones, S, Juste, A, Kallweit, S, Kaluza, A, Kardos, A, Karlberg, A, Kassabov, Z, Kauer, N, Kazakov, D, Kerner, M, Kilian, W, Kling, F, Köneke, K, Kogler, R, Konoplich, R, Kortner, S, Kraml, S, Krause, C, Krauss, F, Krawczyk, M, Kulesza, A, Kuttimalai, S, Lane, R, Lazopoulos, A, Lee, G, Lenzi, P, Lewis, I, Li, Y, Liebler, S, Lindert, J, Liu, X, Liu, Z, Llanes-Estrada, F, Logan, H, Lopez-Val, D, Low, I, Luisoni, G, Maierhöfer, P, Maina, E, Mansoulié, B, Mantler, H, Mantoani, M, Marini, A, Martinez Outschoorn, V, Marzani, S, Marzocca, D, Massironi, A, Mawatari, K, Mazzitelli, J, Mccarn, A, Mellado, B, Melnikov, K, Menari, S, Merlo, L, Meyer, C, Milenovic, P, Mimasu, K, Mishima, S, Mistlberger, B, Moch, S, Mohammadi, A, Monni, P, Montagna, G, Moreno Llácer, M, Moretti, N, Moretti, S, Motyka, L, Mück, A, Mühlleitner, M, Munir, S, Musella, P, Nadolsky, P, Napoletano, D, Nebot, M, Neu, C, Neubert, M, Nevzorov, R, Nicrosini, O, Nielsen, J, Nikolopoulos, K, No, J, O'Brien, C, Ohl, T, Oleari, C, Orimoto, T, Pagani, D, Pandini, C, Papaefstathiou, A, Papanastasiou, A, Passarino, G, Pecjak, B, Pelliccioni, M, Perez, G, Perrozzi, L, Petriello, F, Petrucciani, G, Pianori, E, Piccinini, F, Pierini, M, Pilkington, A, Plätzer, S, Plehn, T, Podskubka, R, Potter, C, Pozzorini, S, Prokofiev, K, Pukhov, A, Puljak, I, Queitsch-Maitland, M, Quevillon, J, Rathlev, D, Rauch, M, Re, E, Rebelo, M, Rebuzzi, D, Reina, L, Reuschle, C, Reuter, J, Riembau, M, Riva, F, Rizzi, A, Robens, T, Röntsch, R, Rojo, J, Romão, J, Rompotis, N, Roskes, J, Roth, R, Salam, G, Salerno, R, Sampaio, M, Santos, R, Sanz, V, Sanz-Cillero, J, Sargsyan, H, Sarica, U, Schichtel, P, Schlenk, J, Schmidt, T, Schmitt, C, Schönherr, M, Schubert, U, Schulze, M, Sekula, S, Sekulla, M, Shabalina, E, Shao, H, Shelton, J, Shepherd-Themistocleous, C, Shim, S, Siegert, F, Signer, A, Silva, J, Silvestrini, L, Sjodahl, M, Slavich, P, Slawinska, M, Soffi, L, Spannowsky, M, Speckner, C, Sperka, D, Spira, M, Stål, O, Staub, F, Stebel, T, Stefaniak, T, Steinhauser, M, Stewart, I, Strassler, M, Streicher, J, Strom, D, Su, S, Sun, X, Tackmann, F, Tackmann, K, Teixeira, A, Teixeira de Lima, R, Theeuwes, V, Thorne, R, Tommasini, D, Torrielli, P, Tosi, M, Tramontano, F, Trócsányi, Z, Trott, M, Tsinikos, I, Ubiali, M, Vanlaer, P, Verkerke, W, Vicini, A, Viliani, L, Vryonidou, E, Wackeroth, D, Wagner, C, Wang, J, Wayand, S, Weiglein, G, Weiss, C, Wiesemann, M, Williams, C, Winter, J, Winterbottom, D, Wolf, R, Xiao, M, Yang, L, Yohay, R, Yuen, S, Zanderighi, G, Zaro, M, Zeppenfeld, D, Ziegler, R, Zirke, T, Zupan, J, de Florian, D, Grojean, C, Maltoni, F, Mariotti, C, Nikitenko, A, Pieri, M, Savard, P, Schumacher, M, Tanaka, R, Ellis, R, and Sjödahl, M

Subjects
High Energy Physics Experiment, High Energy Physics Phenomenology
Abstract

The production of a Standard Model Higgs boson in association with two hard jets in the forward and backward regions of the detector, frequently quoted as the “vector-boson fusion” (VBF) channel, and the production of a Higgs boson in association with a W or Z boson, known as “VH production” or “Higgsstrahlung”, represent cornerstones in a comprehensive study of Higgs boson couplings at the LHC. These production channels do not only provide valuable information on the couplings of Higgs bosons to the massive gauge bosons by themselves, but also allow for the isolation of the Higgs boson decays into -lepton or bottom-quark pairs, whose investigation is essential in the Higgs boson couplings analysis. In the previous reports [7–9], state-of-the-art predictions and error estimates for the total and differential cross sections for pp ! H + 2 jets and pp ! HV ! H + 2 leptons were compiled (with V = W; Z), but the process of improving and refining predictions is still ongoing, even within the Standard Model. In this contribution we update the cross-section predictions for VBF and VH production, covering integrated total and fiducial cross sections as well as differential distributions. In detail, the presented state-of-the-art predictions include QCD corrections up to next-to-next-to-leading order (NNLO), electroweak (EW) corrections up to next-to-leading order (NLO), and contributions from specific partonic channels that open at higher perturbative orders, such as photon-induced collisions or gluon-fusion contributions. Apart from collecting numerical results, we give recommendations as to how to combine the individual components and to assess conservative estimates of remaining theoretical uncertainties. Moreover, issues connected to the matching and the impact of parton showers (PS) are discussed.

Published
2017

9. The Segment Anything foundation model achieves favorable brain tumor auto-segmentation accuracy in MRI to support radiotherapy treatment planning.

Author

Putz F, Beirami S, Schmidt MA, May MS, Grigo J, Weissmann T, Schubert P, Höfler D, Gomaa A, Hassen BT, Lettmaier S, Frey B, Gaipl US, Distel LV, Semrau S, Bert C, Fietkau R, and Huang Y

Abstract

Background: Promptable foundation auto-segmentation models like Segment Anything (SA, Meta AI, New York, USA) represent a novel class of universal deep learning auto-segmentation models that could be employed for interactive tumor auto-contouring in RT treatment planning., Methods: Segment Anything was evaluated in an interactive point-to-mask auto-segmentation task for glioma brain tumor auto-contouring in 16,744 transverse slices from 369 MRI datasets (BraTS 2020 dataset). Up to nine interactive point prompts were automatically placed per slice. Tumor boundaries were auto-segmented on contrast-enhanced T1w sequences. Out of the three auto-contours predicted by SA, accuracy was evaluated for the contour with the highest calculated IoU (Intersection over Union, "oracle mask," simulating interactive model use with selection of the best tumor contour) and for the tumor contour with the highest model confidence ("suggested mask")., Results: Mean best IoU (mbIoU) using the best predicted tumor contour (oracle mask) in full MRI slices was 0.762 (IQR 0.713-0.917). The best 2D mask was achieved after a mean of 6.6 interactive point prompts (IQR 5-9). Segmentation accuracy was significantly better for high- compared to low-grade glioma cases (mbIoU 0.789 vs. 0.668). Accuracy was worse using the suggested mask (0.572). Stacking best tumor segmentations from transverse MRI slices, mean 3D Dice score for tumor auto-contouring was 0.872, which was improved to 0.919 by combining axial, sagittal, and coronal contours., Conclusion: The Segment Anything foundation segmentation model can achieve high accuracy for glioma brain tumor segmentation in MRI datasets. The results suggest that foundation segmentation models could facilitate RT treatment planning when properly integrated in a clinical application., (© 2024. The Author(s).)

Published
2024
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10. End-to-end testing for stereotactic radiotherapy including the development of a Multi-Modality phantom.

Author

Shariff M, Grigo J, Masitho S, Brandt T, Weiss A, Lambrecht U, Stillkrieg W, Lotter M, Putz F, Fietkau R, and Bert C

Subjects
Humans, Equipment Design, Radiotherapy Dosage, Printing, Three-Dimensional, Magnetic Resonance Imaging instrumentation, Magnetic Resonance Imaging methods, Tomography, X-Ray Computed, Radiotherapy Planning, Computer-Assisted methods, Phantoms, Imaging, Radiosurgery instrumentation, Radiosurgery methods
Abstract

Purpose: A new insert for a commercially available end-to-end test phantom was designed and in-house manufactured by 3D printing. Subsequently, the insert was tested for different stereotactic radiation therapy workflows (SRS, SBRT, FSRT, and Multimet) also in comparison to the original insert., Material and Methods: Workflows contained imaging (MR, CT), treatment planning, positioning, and irradiation. Positioning accuracy was evaluated for non-coplanar x-ray, kV- and MV-CBCT systems, as well as surface guided radiation therapy. Dosimetric accuracy of the irradiation was measured with an ionization chamber at four different linear accelerators including dynamic tumor tracking for SBRT., Results: CT parameters of the insert were within the specification. For MR images, the new insert allowed quantitative analysis of the MR distortion. Positioning accuracy of the phantom with the new insert using the imaging systems of the different linacs was < 1 mm/degree also for MV-CBCT and a non-coplanar imaging system which caused > 3 mm deviation with the original insert. Deviation of point dose values was <3% for SRS, FSRT, and SBRT for both inserts. For the Multimet plans deviations exceeded 10% because the ionization chamber was not positioned in each metastasis, but in the center of phantom and treatment plan., Conclusion: The in-house manufactured insert performed well in all steps of four stereotactic treatment end-to-end tests. Advantages over the commercially available alternative were seen for quantitative analysis of deformation correction in MR images, applicability for non-coplanar x-ray imaging, and dynamic tumor tracking., (Copyright © 2022 The Authors. Published by Elsevier GmbH.. All rights reserved.)

Published
2024
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11. "sCT-Feasibility" - a feasibility study for deep learning-based MRI-only brain radiotherapy.

Author

Grigo J, Szkitsak J, Höfler D, Fietkau R, Putz F, and Bert C

Subjects
Humans, Feasibility Studies, Retrospective Studies, Radiotherapy Planning, Computer-Assisted methods, Radiotherapy Dosage, Magnetic Resonance Imaging methods, Brain diagnostic imaging, Deep Learning, Radiotherapy, Intensity-Modulated methods, Brain Neoplasms diagnostic imaging, Brain Neoplasms radiotherapy
Abstract

Background: Radiotherapy (RT) is an important treatment modality for patients with brain malignancies. Traditionally, computed tomography (CT) images are used for RT treatment planning whereas magnetic resonance imaging (MRI) images are used for tumor delineation. Therefore, MRI and CT need to be registered, which is an error prone process. The purpose of this clinical study is to investigate the clinical feasibility of a deep learning-based MRI-only workflow for brain radiotherapy, that eliminates the registration uncertainty through calculation of a synthetic CT (sCT) from MRI data., Methods: A total of 54 patients with an indication for radiation treatment of the brain and stereotactic mask immobilization will be recruited. All study patients will receive standard therapy and imaging including both CT and MRI. All patients will receive dedicated RT-MRI scans in treatment position. An sCT will be reconstructed from an acquired MRI DIXON-sequence using a commercially available deep learning solution on which subsequent radiotherapy planning will be performed. Through multiple quality assurance (QA) measures and reviews during the course of the study, the feasibility of an MRI-only workflow and comparative parameters between sCT and standard CT workflow will be investigated holistically. These QA measures include feasibility and quality of image guidance (IGRT) at the linear accelerator using sCT derived digitally reconstructed radiographs in addition to potential dosimetric deviations between the CT and sCT plan. The aim of this clinical study is to establish a brain MRI-only workflow as well as to identify risks and QA mechanisms to ensure a safe integration of deep learning-based sCT into radiotherapy planning and delivery., Discussion: Compared to CT, MRI offers a superior soft tissue contrast without additional radiation dose to the patients. However, up to now, even though the dosimetrical equivalence of CT and sCT has been shown in several retrospective studies, MRI-only workflows have still not been widely adopted. The present study aims to determine feasibility and safety of deep learning-based MRI-only radiotherapy in a holistic manner incorporating the whole radiotherapy workflow., Trial Registration: NCT06106997., (© 2024. The Author(s).)

Published
2024
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12. Toward a deep learning-based magnetic resonance imaging only workflow for postimplant dosimetry in I-125 seed brachytherapy for prostate cancer.

Author

Grigo J, Karius A, Hanspach J, Mücke L, Laun FB, Huang Y, Strnad V, Fietkau R, Bert C, and Putz F

Subjects
Male, Humans, Iodine Radioisotopes therapeutic use, Workflow, Radiotherapy Dosage, Magnetic Resonance Imaging methods, Contrast Media, Brachytherapy methods, Deep Learning, Prostatic Neoplasms diagnostic imaging, Prostatic Neoplasms radiotherapy, Prostatic Neoplasms pathology
Abstract

Background and Purpose: The current standard imaging-technique for creating postplans in seed prostate brachytherapy is computed tomography (CT), that is associated with additional radiation exposure and poor soft tissue contrast. To establish a magnetic resonance imaging (MRI) only workflow combining improved tissue contrast and high seed detectability, a deep learning-approach for automatic seed segmentation on MRI-scans was developed., Material and Methods: Patients treated with I-125 seed brachytherapy received a postplan-CT and a 1.5 T MRI-scan on nominal day 30 after implantation. For MRI-based seed visualization, DIXON-sequences were acquired and deep learning-based quantitative susceptibility maps (QSM) were generated from 3D-gradient-echo-sequences from 20 patients. Seed segmentations created on CT served as ground truth. For automatic seed segmentation on MRI, a 3D nnU-net model was trained using QSM and DIXON, both solely and combined., Results: Of the implanted seeds 94.8 ± 2.4% were detected with deep learning automatic segmentation entrained on both QSM and DIXON data. Models trained on the individual sequence data-sets performed worse with detection rates of 87.5 ± 2.6% or 88.6 ± 7.5% for QSM and DIXON respectively. The seed centers identified on CT versus QSM and DIXON were on average 1.8 ± 1.3 mm apart. Postimplant dosimetry for evaluation of positioning inaccuracies revealed only small variations of up to 0.4 ± 4.26 Gy in D90 (dose 90% of the prostate receives) between the standard CT-approach and our MRI-only workflow., Conclusion: The proposed deep learning-based MRI-only workflow provided a promisingly accurate and robust seed localization and thus has the potential to compete with current state-of-the-art CT-based postimplant dosimetry in the future., (Copyright © 2023 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.)

Published
2024
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13. Quality requirements for MRI simulation in cranial stereotactic radiotherapy: a guideline from the German Taskforce "Imaging in Stereotactic Radiotherapy".

Author

Putz F, Bock M, Schmitt D, Bert C, Blanck O, Ruge MI, Hattingen E, Karger CP, Fietkau R, Grigo J, Schmidt MA, Bäuerle T, and Wittig A

Subjects
Humans, Magnetic Resonance Imaging, Radiotherapy Dosage, Imaging, Three-Dimensional, Radiosurgery methods, Radiation Oncology
Abstract

Accurate Magnetic Resonance Imaging (MRI) simulation is fundamental for high-precision stereotactic radiosurgery and fractionated stereotactic radiotherapy, collectively referred to as stereotactic radiotherapy (SRT), to deliver doses of high biological effectiveness to well-defined cranial targets. Multiple MRI hardware related factors as well as scanner configuration and sequence protocol parameters can affect the imaging accuracy and need to be optimized for the special purpose of radiotherapy treatment planning. MRI simulation for SRT is possible for different organizational environments including patient referral for imaging as well as dedicated MRI simulation in the radiotherapy department but require radiotherapy-optimized MRI protocols and defined quality standards to ensure geometrically accurate images that form an impeccable foundation for treatment planning. For this guideline, an interdisciplinary panel including experts from the working group for radiosurgery and stereotactic radiotherapy of the German Society for Radiation Oncology (DEGRO), the working group for physics and technology in stereotactic radiotherapy of the German Society for Medical Physics (DGMP), the German Society of Neurosurgery (DGNC), the German Society of Neuroradiology (DGNR) and the German Chapter of the International Society for Magnetic Resonance in Medicine (DS-ISMRM) have defined minimum MRI quality requirements as well as advanced MRI simulation options for cranial SRT., (© 2023. The Author(s).)

Published
2024
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14. Benchmarking ChatGPT-4 on a radiation oncology in-training exam and Red Journal Gray Zone cases: potentials and challenges for ai-assisted medical education and decision making in radiation oncology.

Author

Huang Y, Gomaa A, Semrau S, Haderlein M, Lettmaier S, Weissmann T, Grigo J, Tkhayat HB, Frey B, Gaipl U, Distel L, Maier A, Fietkau R, Bert C, and Putz F

Abstract

Purpose: The potential of large language models in medicine for education and decision-making purposes has been demonstrated as they have achieved decent scores on medical exams such as the United States Medical Licensing Exam (USMLE) and the MedQA exam. This work aims to evaluate the performance of ChatGPT-4 in the specialized field of radiation oncology., Methods: The 38th American College of Radiology (ACR) radiation oncology in-training (TXIT) exam and the 2022 Red Journal Gray Zone cases are used to benchmark the performance of ChatGPT-4. The TXIT exam contains 300 questions covering various topics of radiation oncology. The 2022 Gray Zone collection contains 15 complex clinical cases., Results: For the TXIT exam, ChatGPT-3.5 and ChatGPT-4 have achieved the scores of 62.05% and 78.77%, respectively, highlighting the advantage of the latest ChatGPT-4 model. Based on the TXIT exam, ChatGPT-4's strong and weak areas in radiation oncology are identified to some extent. Specifically, ChatGPT-4 demonstrates better knowledge of statistics, CNS & eye, pediatrics, biology, and physics than knowledge of bone & soft tissue and gynecology, as per the ACR knowledge domain. Regarding clinical care paths, ChatGPT-4 performs better in diagnosis, prognosis, and toxicity than brachytherapy and dosimetry. It lacks proficiency in in-depth details of clinical trials. For the Gray Zone cases, ChatGPT-4 is able to suggest a personalized treatment approach to each case with high correctness and comprehensiveness. Importantly, it provides novel treatment aspects for many cases, which are not suggested by any human experts., Conclusion: Both evaluations demonstrate the potential of ChatGPT-4 in medical education for the general public and cancer patients, as well as the potential to aid clinical decision-making, while acknowledging its limitations in certain domains. Owing to the risk of hallucinations, it is essential to verify the content generated by models such as ChatGPT for accuracy., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Huang, Gomaa, Semrau, Haderlein, Lettmaier, Weissmann, Grigo, Tkhayat, Frey, Gaipl, Distel, Maier, Fietkau, Bert and Putz.)

Published
2023
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15. Synthetic CTs for MRI-only brain RT treatment: integration of immobilization systems.

Author

Masitho S, Grigo J, Brandt T, Lambrecht U, Szkitsak J, Weiss A, Fietkau R, Putz F, and Bert C

Subjects
Humans, Retrospective Studies, Radiotherapy Dosage, Brain diagnostic imaging, Radiotherapy Planning, Computer-Assisted methods, Magnetic Resonance Imaging methods
Abstract

Purpose: Auxiliary devices such as immobilization systems should be considered in synthetic CT (sCT)-based treatment planning (TP) for MRI-only brain radiotherapy (RT). A method for auxiliary device definition in the sCT is introduced, and its dosimetric impact on the sCT-based TP is addressed., Methods: T1-VIBE DIXON was acquired in an RT setup. Ten datasets were retrospectively used for sCT generation. Silicone markers were used to determine the auxiliary devices' relative position. An auxiliary structure template (AST) was created in the TP system and placed manually on the MRI. Various RT mask characteristics were simulated in the sCT and investigated by recalculating the CT-based clinical plan on the sCT. The influence of auxiliary devices was investigated by creating static fields aimed at artificial planning target volumes (PTVs) in the CT and recalculated in the sCT. The dose covering 50% of the PTV (D 50 ) deviation percentage between CT-based/recalculated plan (∆D 50 [%]) was evaluated., Results: Defining an optimal RT mask yielded a ∆D 50 [%] of 0.2 ± 1.03% for the PTV and between -1.6 ± 3.4% and 1.1 ± 2.0% for OARs. Evaluating each static field, the largest ∆D 50 [%] was delivered by AST positioning inaccuracy (max: 3.5 ± 2.4%), followed by the RT table (max: 3.6 ± 1.2%) and the RT mask (max: 3.0 ± 0.8% [anterior], 1.6 ± 0.4% [rest]). No correlation between ∆D 50 [%] and beam depth was found for the sum of opposing beams, except for (45° + 315°)., Conclusion: This study evaluated the integration of auxiliary devices and their dosimetric influence on sCT-based TP. The AST can be easily integrated into the sCT-based TP. Further, we found that the dosimetric impact was within an acceptable range for an MRI-only workflow., (© 2023. The Author(s).)

Published
2023
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16. Usability of magnetic resonance images acquired at a novel low-field 0.55 T scanner for brain radiotherapy treatment planning.

Author

Grigo J, Masitho S, Fautz HP, Voigt R, Schonath M, Oleszczuk A, Uder M, Heiss R, Fietkau R, Putz F, and Bert C

Abstract

Background and Purpose: Low-field magnetic resonance imaging (MRI) may offer specific advantages over high-field MRI, e.g. lower susceptibility-dependent distortions and simpler installation. The study aim was to evaluate if a novel 0.55 T MRI scanner provides sufficient image accuracy and quality for radiotherapy (RT) treatment planning., Material and Methods: The geometric accuracy of images acquired at a low-field MRI scanner was evaluated in phantom measurements regarding gradient non-linearity-related distortions. Patient-induced B0-susceptibility changes were investigated via B0-field-mapping in ten volunteers. Patients were positioned in RT-setup using a 3D-printed insert for the head/neck-coil that was tested for sufficient signal-to-noise-ratio (SNR). The suitability of the MRI-system for detection of metastases was evaluated in eleven patients. In comparison to diagnostic images, acquired at ≥1.5 T, three physicians evaluated the detectability of metastases by counting them in low- and high-field-images, respectively., Results: The phantom measurements showed a high imaging fidelity after 3D-distortion-correction with (1.2 ± 0.9) mm geometric distortion in 10 cm radius from isocentre. At the edges remaining distortions were greater than at 1.5 T. The mean susceptibility-induced distortions in the head were (0.05 ± 0.05) mm and maximum 0.69 mm. SNR analysis showed that optimised positioning of RT-patients without signal loss in the head/neck-coil was possible with the RT-insert. No significant differences (p = 0.48) in detectability of metastases were found., Conclusion: The 0.55 T MRI system provided sufficiently geometrically accurate and high-resolution images that can be used for RT-planning for brain metastases. Hence, modern low-field MRI may contribute to simply access MRI for RT-planning after further investigations., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Universitätsklinikum Erlangen, Strahlenklinik and Siemens Healthineers (Erlangen, Germany) have institutional research contracts partly related to this work., (© 2023 The Authors.)

Published
2023
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17. Feasibility of artificial-intelligence-based synthetic computed tomography in a magnetic resonance-only radiotherapy workflow for brain radiotherapy: Two-way dose validation and 2D/2D kV-image-based positioning.

Author

Masitho S, Szkitsak J, Grigo J, Fietkau R, Putz F, and Bert C

Abstract

Background and Purpose: Magnetic Resonance Imaging (MRI)-only workflow eliminates the MRI-computed tomography (CT) registration inaccuracy, which degrades radiotherapy (RT) treatment accuracy. For an MRI-only workflow MRI sequences need to be converted to synthetic-CT (sCT). The purpose of this study was to evaluate a commercially available artificial intelligence (AI)-based sCT generation for dose calculation and 2D/2D kV-image daily positioning for brain RT workflow., Materials and Methods: T1-VIBE DIXON was acquired at the 1.5 T MRI for 26 patients in RT setup for sCTs generation. For each patient, a volumetric modulated arc therapy (VMAT) plan was optimized on the CT, then recalculated on the sCT; and vice versa. sCT-based digitally reconstructed radiographs (DRRs) were fused with stereoscopic X-ray images recorded as image guidance for clinical treatments. Dosimetric differences between planned/recalculated doses and the differences between the calculated and recorded clinical couch shift/rotation were evaluated., Results: Mean ΔD 50 between planned/recalculated doses for target volumes ranged between -0.2 % and 0.2 %; mean ΔD 50 and ΔD 0.01ccm were -0.6 % and 1.6 % and -1.4 % and 1.0 % for organ-at-risks, respectively. Differences were tested for clinical equivalence using intervals ±2 % (dose), ±1mm (translation), and ±1° (rotation). Dose equivalence was found using ±2 % interval ( p  < 0.001). The median differences between lat./long./vert. couch shift between CT-based/sCT-based DRRs were 0.3 mm/0.2 mm/0.3 mm ( p  < 0.05); median differences between lat./long./vert. couch rotation were -1.5°/0.1°/0.1° (after improvement of RT setup: -0.4°/-0.1°/-0.4°, p  < 0.05)., Conclusions: This in-silico study showed that the AI-based sCT provided equivalent results to the CT for dose calculation and daily stereoscopic X-ray positioning when using an optimal RT setup during MRI acquisition., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 The Author(s).)

Published
2022
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18. Deep learning-based quantitative susceptibility mapping (QSM) in the presence of fat using synthetically generated multi-echo phase training data.

Author

Hanspach J, Bollmann S, Grigo J, Karius A, Uder M, and Laun FB

Subjects
Algorithms, Brain diagnostic imaging, Brain Mapping, Humans, Image Processing, Computer-Assisted methods, Magnetic Resonance Imaging methods, Male, Water, Deep Learning, Iodine Radioisotopes
Abstract

Purpose: To enable a fast and automatic deep learning-based QSM reconstruction of tissues with diverse chemical shifts, relevant to most regions outside the brain., Methods: A UNET was trained to reconstruct susceptibility maps using synthetically generated, unwrapped, multi-echo phase data as input. The RMS error with respect to synthetic validation data was computed. The method was tested on two in vivo knee and two pelvis data sets. Comparisons were made to a conventional fat-water separation pipeline by applying a commonly used graph-cut algorithm, both without and with an extended mask for background field removal (FWS-CONV-QSM and FWS-MASK-CONV-QSM, respectively). Several regions of interest were segmented and compared. Furthermore, the approach was tested on a prostate cancer patient receiving low-dose-rate brachytherapy, to detect and localize the seeds by MRI., Results: The RMS error was 0.292 ppm with FWS-CONV-QSM and 0.123 ppm for the UNET approach. Susceptibility maps were reconstructed much faster (< 10 s) and completely automatically (no background masking needed) by the UNET compared with the other applied techniques (5 min 51 s and 22 min 44 s for CONV-QSM and FWS-MASK-CONV-QSM, respectively. Background artifacts, fat-water swaps, and hypointense artifacts between I-125 seeds of a patient receiving low-dose brachytherapy in the prostate were largely reduced in the UNET approach., Conclusions: Deep learning-based QSM reconstruction, trained solely with synthetic data, is well-suited to rapidly reconstructing high-quality susceptibility maps in the presence of fat without needing masking for background field removal., (© 2022 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

Published
2022
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19. Permanent LDR prostate brachytherapy: Comprehensive characterization of seed-dynamics within the prostate on a seed-only level.

Author

Karius A, Lotter M, Kreppner S, Schaller V, Lubgan D, Grigo J, Fietkau R, Strnad V, and Bert C

Subjects
Humans, Male, Prostate diagnostic imaging, Radiotherapy Dosage, Radiotherapy Planning, Computer-Assisted, Rectum, Brachytherapy methods, Prostatic Neoplasms diagnostic imaging, Prostatic Neoplasms radiotherapy
Abstract

Purpose: Seed brachytherapy is a well-established treatment modality for prostate cancer. However, there is still a lack of profound characterizations of seed motions within the prostate. We assessed these dynamics between day 0 and day 30 of brachytherapy., Methods: We considered 45 patients with 2408 implanted seeds, and performed a 1:1 assignment between their positions on post-plan CT (nominal day 30) and intraoperative ultrasound (day 0). Geometric seed arrangement changes were measured for each patient and the entire collective. The impact of seed strand-lengths and implant regions was investigated. Correlations with patient characteristics were evaluated. We determined corresponding dosimetric effects by calculating common dose metrics., Results: We found a median seed displacement of 4.3 mm [interquartile range: 3.1-6.9 mm], occurring preferentially in superior-inferior direction. Single and double strands moved significantly stronger than strands of higher lengths. Seed dynamics was more pronounced in base (5.6 mm [3.7-10.7 mm]) and apex (6.5 mm [4.1-15.0 mm]) than in the mid-gland (3.8 mm [2.7-5.0 mm]), and less pronounced in peripheral (4.3 mm [3.0-6.7 mm]) than in urethra-near (5.5 mm [3.5-10.7 mm]) regions. Correlations of seed dynamics with prostate volume changes and the number of implanted seeds and needles were found. D 90 (dose that 90% of the prostate receives) varied by a median of 3 Gy [-6 to 15 Gy] between treatment plan and post-plan, but >40 Gy for individual patients., Conclusions: Reducing seed dynamics is important to ensure a high treatment quality. For this, strands containing ≥3 seeds may be useful, implantations in base-, apex-, and urethra-near zone should be avoided, and the number of needles and seeds may be minimized where possible., (Copyright © 2022 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.)

Published
2022
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20. Staphylococcal micrococcins. II. Isolation, purification and identification.

Author

Breiter J, Metz H, and Grigo J

Subjects
Anti-Bacterial Agents analysis, Anti-Bacterial Agents biosynthesis, Chromatography, Gel, Fermentation, Hydrogen-Ion Concentration, Micrococcaceae analysis, Solubility, Temperature, Time Factors, Anti-Bacterial Agents isolation & purification, Micrococcaceae metabolism
Abstract

Seven strains belonging to the Micrococcaceae family and excreting substances with antibiotic activity, were grown in submerged cultures on technical scale for isolation, purification and identification of biologically active compounds. Two basic substances were isolated and classified to the micrococcin antibiotics family. The naturally occurring mixture of micrococcin M1 and M3 was called micrococcin M. This antibiotic has the formula C48H50O11N12S6 and a molecular weight of about 1160, melting point 221--224 degrees C, and optical rotation [a]20/D = + 66.6. Other antibiotically active substances produced by seven investigated strains were identified as micrococcin M or as separate compounds. Comparison with previously described micrococcin and micrococcin P has been made.

Published
1975

21. [Microorganisms in drugs and cosmetics - occurrence, harms and consequences in hygienic manufacturing (author's transl)].

Author

Grigo J

Subjects
Bacteria growth & development, Drug Packaging, Drug Storage, Fungi growth & development, Species Specificity, Bacteria isolation & purification, Cosmetics, Drug Contamination prevention & control, Fungi isolation & purification, Technology, Pharmaceutical
Abstract

The quantity of pharmaceutical and cosmetic products with different composition and the diversity of contaminating microorganisms set up special problems for each product with its specific field of application. It is not exact to generalize the hazard of contaminating microorganisms to product cathegories. Some product cathegories however are more imperilled to be contaminated with microorganisms and they are more hazardous than other ones. The most important component of the living matter is water that decides on growth, multiplication and survival of microorganisms in drugs and cosmetics. Products with a high content of available water are the most problematic ones. The consequences of survival and multiplication of microorganisms in relation to metabolic activity, pathogenicity and route of administration can be harmless or fatal. The nutritive wants of many microorganisms are very small, even simple salt solutions do not exclude microbial growth. There scarcely exist substrates not used as energy source by any microorganism and so it does not wonder that desinfectants are also used. Added preservatives may be absorbed or inactivated by suspended anorganic components, swelling agents, solubilizers etc., the containers or its closing. In the water phase of emulsions, in which under special conditions smaller amounts of the preservative are available, microorganisms sometimes can multiply. Skin care products neither belonging to pharmaceuticals nor to cosmetics present special clinical problems. Many times creams and lotions contain ingredients metabolized by microorganisms. Ointments and oils can be overgrown only by highly specialized organisms but if there is condensed water as a film at boundary surfaces much more microorganism species can grow. When using cosmetics it must be considered that parts of them will get into the eye. The eye is really endangered by Pseudomonads, which can according to the composition multiply in shampoos and whose contact to the eye can not be excluded. Syrups and solutions contain sugar concentrations, which suppress growth of most microorganisms except osmotolerant germs. Because of their low water content powders normally are protected against microbial growth but they should be free from clostridial spores for a mixture of powder and sweat is a good nutrient medium to Clostridia and fungi. Powders for surgical use must be sterile. Tablets and dragees do not allow microbial multiplication because of their low water activity. Under bad storage conditions a local increase of water content may permit microbial growth at the surface, especially in hygroscopicity. Fortunately there is seen a trend of not using multi-dose-containers for injections because of the high risk of contamination. It is to develop single-dose-containers also for other groups of preparations especially for eye-preparations. Many products microbiologically unobjectionable produced are contaminated in use, they contain the spectrum of microorganisms of the area of application...

Published
1976

22. [Biological indicators for the control of autoclave function: some theoretical aspects and practical experience in their development and application].

Author

Costin ID and Grigo J

Subjects
Bacillus subtilis, Cell Count, Cell Survival, Clostridium, Culture Media, Disinfectants, Ethylene Oxide, Radiation Effects, Spores, Bacterial growth & development, Spores, Bacterial isolation & purification, Sterilization methods, Water, Bacillus growth & development, Bacillus isolation & purification, Hot Temperature, Sterilization standards
Published
1974

23. [The distribution of a Shigella dysenteriae exotoxin in the experimental animal].

Author

Gärtner H and Grigo J

Subjects
Animals, Central Nervous System metabolism, Female, Injections, Intravenous, Intestine, Small metabolism, Iodine Isotopes, Kidney metabolism, Liver metabolism, Lung metabolism, Medulla Oblongata metabolism, Muscles metabolism, Organ Specificity, Rabbits, Spinal Cord metabolism, Spleen metabolism, Thyroid Gland metabolism, Time Factors, Toxins, Biological blood, Toxins, Biological isolation & purification, Shigella dysenteriae, Toxins, Biological metabolism
Published
1969

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