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Hwang EJ, Park JE, Song KD, Yang DH, Kim KW, Lee JG, Yoon JH, Han K, Kim DH, Kim H, Park CM. 2023 Survey on User Experience of Artificial Intelligence Software in Radiology by the Korean Society of Radiology. Korean J Radiol 2024; 25:613-622. [PMID: 38942455 DOI: 10.3348/kjr.2023.1246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 04/24/2024] [Accepted: 04/26/2024] [Indexed: 06/30/2024] Open
Abstract
OBJECTIVE In Korea, radiology has been positioned towards the early adoption of artificial intelligence-based software as medical devices (AI-SaMDs); however, little is known about the current usage, implementation, and future needs of AI-SaMDs. We surveyed the current trends and expectations for AI-SaMDs among members of the Korean Society of Radiology (KSR). MATERIALS AND METHODS An anonymous and voluntary online survey was open to all KSR members between April 17 and May 15, 2023. The survey was focused on the experiences of using AI-SaMDs, patterns of usage, levels of satisfaction, and expectations regarding the use of AI-SaMDs, including the roles of the industry, government, and KSR regarding the clinical use of AI-SaMDs. RESULTS Among the 370 respondents (response rate: 7.7% [370/4792]; 340 board-certified radiologists; 210 from academic institutions), 60.3% (223/370) had experience using AI-SaMDs. The two most common use-case of AI-SaMDs among the respondents were lesion detection (82.1%, 183/223), lesion diagnosis/classification (55.2%, 123/223), with the target imaging modalities being plain radiography (62.3%, 139/223), CT (42.6%, 95/223), mammography (29.1%, 65/223), and MRI (28.7%, 64/223). Most users were satisfied with AI-SaMDs (67.6% [115/170, for improvement of patient management] to 85.1% [189/222, for performance]). Regarding the expansion of clinical applications, most respondents expressed a preference for AI-SaMDs to assist in detection/diagnosis (77.0%, 285/370) and to perform automated measurement/quantification (63.5%, 235/370). Most respondents indicated that future development of AI-SaMDs should focus on improving practice efficiency (81.9%, 303/370) and quality (71.4%, 264/370). Overall, 91.9% of the respondents (340/370) agreed that there is a need for education or guidelines driven by the KSR regarding the use of AI-SaMDs. CONCLUSION The penetration rate of AI-SaMDs in clinical practice and the corresponding satisfaction levels were high among members of the KSR. Most AI-SaMDs have been used for lesion detection, diagnosis, and classification. Most respondents requested KSR-driven education or guidelines on the use of AI-SaMDs.
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Acharya S, Adamová D, Aglieri Rinella G, Aglietta L, Agnello M, Agrawal N, Ahammed Z, Ahmad S, Ahn SU, Ahuja I, Akindinov A, Al-Turany M, Aleksandrov D, Alessandro B, Alfanda HM, Alfaro Molina R, Ali B, Alici A, Alizadehvandchali N, Alkin A, Alme J, Alocco G, Alt T, Altamura AR, Altsybeev I, Alvarado JR, Anaam MN, Andrei C, Andreou N, Andronic A, Andronov E, Anguelov V, Antinori F, Antonioli P, Apadula N, Aphecetche L, Appelshäuser H, Arata C, Arcelli S, Aresti M, Arnaldi R, Arneiro JGMCA, Arsene IC, Arslandok M, Augustinus A, Averbeck R, Azmi MD, Baba H, Badalà A, Bae J, Baek YW, Bai X, Bailhache R, Bailung Y, Bala R, Balbino A, Baldisseri A, Balis B, Banerjee D, Banoo Z, Barile F, Barioglio L, Barlou M, Barman B, Barnaföldi GG, Barnby LS, Barreau E, Barret V, Barreto L, Bartels C, Barth K, Bartsch E, Bastid N, Basu S, Batigne G, Battistini D, Batyunya B, Bauri D, Bazo Alba JL, Bearden IG, Beattie C, Becht P, Behera D, Belikov I, Bell Hechavarria ADC, Bellini F, Bellwied R, Belokurova S, Beltran LGE, Beltran YAV, Bencedi G, Beole S, Berdnikov Y, Berdnikova A, Bergmann L, Besoiu MG, Betev L, Bhaduri PP, Bhasin A, Bhat MA, Bhattacharjee B, Bianchi L, Bianchi N, Bielčík J, Bielčíková J, Bigot AP, Bilandzic A, Biro G, Biswas S, Bize N, Blair JT, Blau D, Blidaru MB, Bluhme N, Blume C, Boca G, Bock F, Bodova T, Boi S, Bok J, Boldizsár L, Bombara M, Bond PM, Bonomi G, Borel H, Borissov A, Borquez Carcamo AG, Bossi H, Botta E, Bouziani YEM, Bratrud L, Braun-Munzinger P, Bregant M, Broz M, Bruno GE, Buckland MD, Budnikov D, Buesching H, Bufalino S, Buhler P, Burmasov N, Buthelezi Z, Bylinkin A, Bysiak SA, Cabanillas Noris JC, Cai M, Caines H, Caliva A, Calvo Villar E, Camacho JMM, Camerini P, Canedo FDM, Cantway SL, Carabas M, Carballo AA, Carnesecchi F, Caron R, Carvalho LAD, Castillo Castellanos J, Catalano F, Cattaruzzi S, Ceballos Sanchez C, Cerri R, Chakaberia I, Chakraborty P, Chandra S, Chapeland S, Chartier M, Chattopadhyay S, Chattopadhyay S, Cheng T, Cheshkov C, Chibante Barroso V, Chinellato DD, Chizzali ES, Cho J, Cho S, Chochula P, Choudhury D, Christakoglou P, Christensen CH, Christiansen P, Chujo T, Ciacco M, Cicalo C, Ciupek MR, Clai G, Colamaria F, Colburn JS, Colella D, Colocci M, Concas M, Conesa Balbastre G, Conesa Del Valle Z, Contin G, Contreras JG, Coquet ML, Cortese P, Cosentino MR, Costa F, Costanza S, Cot C, Crkovská J, Crochet P, Cruz-Torres R, Cui P, Dainese A, Danisch MC, Danu A, Das P, Das P, Das S, Dash AR, Dash S, De Caro A, de Cataldo G, de Cuveland J, De Falco A, De Gruttola D, De Marco N, De Martin C, De Pasquale S, Deb R, Del Grande R, Dello Stritto L, Deng W, Dhankher P, Di Bari D, Di Mauro A, Diab B, Diaz RA, Dietel T, Ding Y, Ditzel J, Divià R, Dixit DU, Djuvsland Ø, Dmitrieva U, Dobrin A, Dönigus B, Dubinski JM, Dubla A, Dudi S, Dupieux P, Durkac M, Dzalaiova N, Eder TM, Ehlers RJ, Eisenhut F, Ejima R, Elia D, Erazmus B, Ercolessi F, Espagnon B, Eulisse G, Evans D, Evdokimov S, Fabbietti L, Faggin M, Faivre J, Fan F, Fan W, Fantoni A, Fasel M, Feliciello A, Feofilov G, Fernández Téllez A, Ferrandi L, Ferrer MB, Ferrero A, Ferrero C, Ferretti A, Feuillard VJG, Filova V, Finogeev D, Fionda FM, Flatland E, Flor F, Flores AN, Foertsch S, Fokin I, Fokin S, Fragiacomo E, Frajna E, Fuchs U, Funicello N, Furget C, Furs A, Fusayasu T, Gaardhøje JJ, Gagliardi M, Gago AM, Gahlaut T, Galvan CD, Gangadharan DR, Ganoti P, Garabatos C, García Chávez T, Garcia-Solis E, Gargiulo C, Gasik P, Gautam A, Gay Ducati MB, Germain M, Ghimouz A, Ghosh C, Giacalone M, Gioachin G, Giubellino P, Giubilato P, Glaenzer AMC, Glässel P, Glimos E, Goh DJQ, Gonzalez V, Gordeev P, Gorgon M, Goswami K, Gotovac S, Grabski V, Graczykowski LK, Grecka E, Grelli A, Grigoras C, Grigoriev V, Grigoryan S, Grosa F, Grosse-Oetringhaus JF, Grosso R, Grund D, Grunwald NA, Guardiano GG, Guernane R, Guilbaud M, Gulbrandsen K, Gündem T, Gunji T, Guo W, Gupta A, Gupta R, Gupta R, Gwizdziel K, Gyulai L, Hadjidakis C, Haider FU, Haidlova S, Haldar M, Hamagaki H, Hamdi A, Han Y, Hanley BG, Hannigan R, Hansen J, Harris JW, Harton A, Hartung MV, Hassan H, Hatzifotiadou D, Hauer P, Havener LB, Hellbär E, Helstrup H, Hemmer M, Herman T, Herrera Corral G, Herrmann F, Herrmann S, Hetland KF, Heybeck B, Hillemanns H, Hippolyte B, Hoffmann FW, Hofman B, Hong GH, Horst M, Horzyk A, Hou Y, Hristov P, Huhn P, Huhta LM, Humanic TJ, Hutson A, Hutter D, Hwang MC, Ilkaev R, Ilyas H, Inaba M, Innocenti GM, Ippolitov M, Isakov A, Isidori T, Islam MS, Ivanov M, Ivanov M, Ivanov V, Iversen KE, Jablonski M, Jacak B, Jacazio N, Jacobs PM, Jadlovska S, Jadlovsky J, Jaelani S, Jahnke C, Jakubowska MJ, Janik MA, Janson T, Ji S, Jia S, Jimenez AAP, Jonas F, Jones DM, Jowett JM, Jung J, Jung M, Junique A, Jusko A, Kabus MJ, Kaewjai J, Kalinak P, Kalteyer AS, Kalweit A, Karatovic D, Karavichev O, Karavicheva T, Karczmarczyk P, Karpechev E, Kebschull U, Keidel R, Keijdener DLD, Keil M, Ketzer B, Khade SS, Khan AM, Khan S, Khanzadeev A, Kharlov Y, Khatun A, Khuntia A, Khuranova Z, Kileng B, Kim B, Kim C, Kim DJ, Kim EJ, Kim J, Kim J, Kim J, Kim M, Kim S, Kim T, Kimura K, Kirsch S, Kisel I, Kiselev S, Kisiel A, Kitowski JP, Klay JL, Klein J, Klein S, Klein-Bösing C, Kleiner M, Klemenz T, Kluge A, Kobdaj C, Kollegger T, Kondratyev A, Kondratyeva N, Konig J, Konigstorfer SA, Konopka PJ, Kornakov G, Korwieser M, Koryciak SD, Kotliarov A, Kovacic N, Kovalenko V, Kowalski M, Kozhuharov V, Králik I, Kravčáková A, Krcal L, Krivda M, Krizek F, Krizkova Gajdosova K, Kroesen M, Krüger M, Krupova DM, Kryshen E, Kučera V, Kuhn C, Kuijer PG, Kumaoka T, Kumar D, Kumar L, Kumar N, Kumar S, Kundu S, Kurashvili P, Kurepin A, Kurepin AB, Kuryakin A, Kushpil S, Kuskov V, Kutyla M, Kweon MJ, Kwon Y, La Pointe SL, La Rocca P, Lakrathok A, Lamanna M, Landou AR, Langoy R, Larionov P, Laudi E, Lautner L, Lavicka R, Lea R, Lee H, Legrand I, Legras G, Lehrbach J, Lelek TM, Lemmon RC, León Monzón I, Lesch MM, Lesser ED, Lévai P, Li X, Liang-Gilman BE, Lien J, Lietava R, Likmeta I, Lim B, Lim SH, Lindenstruth V, Lindner A, Lippmann C, Liu DH, Liu J, Liveraro GSS, Lofnes IM, Loizides C, Lokos S, Lömker J, Loncar P, Lopez X, López Torres E, Lu P, Lugo FV, Luhder JR, Lunardon M, Luparello G, Ma YG, Mager M, Maire A, Majerz EM, Makariev MV, Malaev M, Malfattore G, Malik NM, Malik QW, Malik SK, Malinina L, Mallick D, Mallick N, Mandaglio G, Mandal SK, Manko V, Manso F, Manzari V, Mao Y, Marcjan RW, Margagliotti GV, Margotti A, Marín A, Markert C, Martinengo P, Martínez MI, Martínez García G, Martins MPP, Masciocchi S, Masera M, Masoni A, Massacrier L, Massen O, Mastroserio A, Matonoha O, Mattiazzo S, Matyja A, Mayer C, Mazuecos AL, Mazzaschi F, Mazzilli M, Mdhluli JE, Melikyan Y, Menchaca-Rocha A, Mendez JEM, Meninno E, Menon AS, Meres M, Miake Y, Micheletti L, Mihaylov DL, Mikhaylov K, Miśkowiec D, Modak A, Mohanty B, Khan MM, Molander MA, Monira S, Mordasini C, Moreira De Godoy DA, Morozov I, Morsch A, Mrnjavac T, Muccifora V, Muhuri S, Mulligan JD, Mulliri A, Munhoz MG, Munzer RH, Murakami H, Murray S, Musa L, Musinsky J, Myrcha JW, Naik B, Nambrath AI, Nandi BK, Nania R, Nappi E, Nassirpour AF, Nath A, Nattrass C, Naydenov MN, Neagu A, Negru A, Nekrasova E, Nellen L, Nepeivoda R, Nese S, Neskovic G, Nicassio N, Nielsen BS, Nielsen EG, Nikolaev S, Nikulin S, Nikulin V, Noferini F, Noh S, Nomokonov P, Norman J, Novitzky N, Nowakowski P, Nyanin A, Nystrand J, Oh S, Ohlson A, Okorokov VA, Oleniacz J, Onnerstad A, Oppedisano C, Ortiz Velasquez A, Otwinowski J, Oya M, Oyama K, Pachmayer Y, Padhan S, Pagano D, Paić G, Paisano-Guzmán S, Palasciano A, Panebianco S, Park H, Park H, Park J, Parkkila JE, Patley Y, Paul B, Paulino MMDM, Pei H, Peitzmann T, Peng X, Pennisi M, Perciballi S, Peresunko D, Perez GM, Pestov Y, Petrov V, Petrovici M, Pezzi RP, Piano S, Pikna M, Pillot P, Pinazza O, Pinsky L, Pinto C, Pisano S, Płoskoń M, Planinic M, Pliquett F, Poghosyan MG, Polichtchouk B, Politano S, Poljak N, Pop A, Porteboeuf-Houssais S, Pozdniakov V, Pozos IY, Pradhan KK, Prasad SK, Prasad S, Preghenella R, Prino F, Pruneau CA, Pshenichnov I, Puccio M, Pucillo S, Pugelova Z, Qiu S, Quaglia L, Ragoni S, Rai A, Rakotozafindrabe A, Ramello L, Rami F, Rancien TA, Rasa M, Räsänen SS, Rath R, Rauch MP, Ravasenga I, Read KF, Reckziegel C, Redelbach AR, Redlich K, Reetz CA, Regules-Medel HD, Rehman A, Reidt F, Reme-Ness HA, Rescakova Z, Reygers K, Riabov A, Riabov V, Ricci R, Richter M, Riedel AA, Riegler W, Riffero AG, Ristea C, Rodriguez MV, Rodríguez Cahuantzi M, Rodríguez Ramírez SA, Røed K, Rogalev R, Rogochaya E, Rogoschinski TS, Rohr D, Röhrich D, Rojas PF, Rojas Torres S, Rokita PS, Romanenko G, Ronchetti F, Rosano A, Rosas ED, Roslon K, Rossi A, Roy A, Roy S, Rubini N, Ruggiano D, Rui R, Russek PG, Russo R, Rustamov A, Ryabinkin E, Ryabov Y, Rybicki A, Rytkonen H, Ryu J, Rzesa W, Saarimaki OAM, Sadhu S, Sadovsky S, Saetre J, Šafařík K, Saha P, Saha SK, Saha S, Sahoo B, Sahoo R, Sahoo S, Sahu D, Sahu PK, Saini J, Sajdakova K, Sakai S, Salvan MP, Sambyal S, Samitz D, Sanna I, Saramela TB, Sarkar D, Sarma P, Sarritzu V, Sarti VM, Sas MHP, Sawan S, Scapparone E, Schambach J, Scheid HS, Schiaua C, Schicker R, Schlepper F, Schmah A, Schmidt C, Schmidt HR, Schmidt MO, Schmidt M, Schmidt NV, Schmier AR, Schotter R, Schröter A, Schukraft J, Schweda K, Scioli G, Scomparin E, Seger JE, Sekiguchi Y, Sekihata D, Selina M, Selyuzhenkov I, Senyukov S, Seo JJ, Serebryakov D, Serkin L, Šerkšnytė L, Sevcenco A, Shaba TJ, Shabetai A, Shahoyan R, Shangaraev A, Sharma B, Sharma D, Sharma H, Sharma M, Sharma S, Sharma S, Sharma U, Shatat A, Sheibani O, Shigaki K, Shimomura M, Shin J, Shirinkin S, Shou Q, Sibiriak Y, Siddhanta S, Siemiarczuk T, Silva TF, Silvermyr D, Simantathammakul T, Simeonov R, Singh B, Singh B, Singh K, Singh R, Singh R, Singh R, Singh S, Singh VK, Singhal V, Sinha T, Sitar B, Sitta M, Skaali TB, Skorodumovs G, Slupecki M, Smirnov N, Snellings RJM, Solheim EH, Song J, Sonnabend C, Sonneveld JM, Soramel F, Soto-Hernandez AB, Spijkers R, Sputowska I, Staa J, Stachel J, Stan I, Steffanic PJ, Stiefelmaier SF, Stocco D, Storehaug I, Stratmann P, Strazzi S, Sturniolo A, Stylianidis CP, Suaide AAP, Suire C, Sukhanov M, Suljic M, Sultanov R, Sumberia V, Sumowidagdo S, Szarka I, Szymkowski M, Taghavi SF, Taillepied G, Takahashi J, Tambave GJ, Tang S, Tang Z, Tapia Takaki JD, Tapus N, Tarasovicova LA, Tarzila MG, Tassielli GF, Tauro A, Tavira García A, Tejeda Muñoz G, Telesca A, Terlizzi L, Terrevoli C, Thakur S, Thomas D, Tikhonov A, Tiltmann N, Timmins AR, Tkacik M, Tkacik T, Toia A, Tokumoto R, Tomohiro K, Topilskaya N, Toppi M, Tork T, Torres PV, Torres VV, Torres Ramos AG, Trifiró A, Triolo AS, Tripathy S, Tripathy T, Trogolo S, Trubnikov V, Trzaska WH, Trzcinski TP, Tumkin A, Turrisi R, Tveter TS, Ullaland K, Ulukutlu B, Uras A, Urioni M, Usai GL, Vala M, Valle N, van Doremalen LVR, van Leeuwen M, van Veen CA, van Weelden RJG, Vande Vyvre P, Varga D, Varga Z, Vasileiou M, Vasiliev A, Vázquez Doce O, Vazquez Rueda O, Vechernin V, Vercellin E, Vergara Limón S, Verma R, Vermunt L, Vértesi R, Verweij M, Vickovic L, Vilakazi Z, Villalobos Baillie O, Villani A, Vinogradov A, Virgili T, Virta MMO, Vislavicius V, Vodopyanov A, Volkel B, Völkl MA, Voloshin SA, Volpe G, von Haller B, Vorobyev I, Vozniuk N, Vrláková J, Wan J, Wang C, Wang D, Wang Y, Wang Y, Wegrzynek A, Weiglhofer FT, Wenzel SC, Wessels JP, Wiechula J, Wikne J, Wilk G, Wilkinson J, Willems GA, Windelband B, Winn M, Wright JR, Wu W, Wu Y, Xu R, Yadav A, Yadav AK, Yamaguchi Y, Yang S, Yano S, Yeats ER, Yin Z, Yoo IK, Yoon JH, Yu H, Yuan S, Yuncu A, Zaccolo V, Zampolli C, Zanone F, Zardoshti N, Zarochentsev A, Závada P, Zaviyalov N, Zhalov M, Zhang B, Zhang C, Zhang L, Zhang S, Zhang X, Zhang Y, Zhang Z, Zhao M, Zherebchevskii V, Zhi Y, Zhong C, Zhou D, Zhou Y, Zhu J, Zhu Y, Zugravel SC, Zurlo N. Emergence of Long-Range Angular Correlations in Low-Multiplicity Proton-Proton Collisions. PHYSICAL REVIEW LETTERS 2024; 132:172302. [PMID: 38728735 DOI: 10.1103/physrevlett.132.172302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 02/22/2024] [Accepted: 03/22/2024] [Indexed: 05/12/2024]
Abstract
This Letter presents the measurement of near-side associated per-trigger yields, denoted ridge yields, from the analysis of angular correlations of charged hadrons in proton-proton collisions at sqrt[s]=13 TeV. Long-range ridge yields are extracted for pairs of charged particles with a pseudorapidity difference of 1.4<|Δη|<1.8 and a transverse momentum of 1
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Acharya S, Adamová D, Adler A, Aglieri Rinella G, Agnello M, Agrawal N, Ahammed Z, Ahmad S, Ahn SU, Ahuja I, Akindinov A, Al-Turany M, Aleksandrov D, Alessandro B, Alfanda HM, Alfaro Molina R, Ali B, Alici A, Alizadehvandchali N, Alkin A, Alme J, Alocco G, Alt T, Altamura AR, Altsybeev I, Alvarado JR, Anaam MN, Andrei C, Andronic A, Anguelov V, Antinori F, Antonioli P, Apadula N, Aphecetche L, Appelshäuser H, Arata C, Arcelli S, Aresti M, Arnaldi R, Arneiro JGMCA, Arsene IC, Arslandok M, Augustinus A, Averbeck R, Azmi MD, Baba H, Badalà A, Bae J, Baek YW, Bai X, Bailhache R, Bailung Y, Balbino A, Baldisseri A, Balis B, Banerjee D, Banoo Z, Barbera R, Barile F, Barioglio L, Barlou M, Barnaföldi GG, Barnby LS, Barret V, Barreto L, Bartels C, Barth K, Bartsch E, Bastid N, Basu S, Batigne G, Battistini D, Batyunya B, Bauri D, Bazo Alba JL, Bearden IG, Beattie C, Becht P, Behera D, Belikov I, Bell Hechavarria ADC, Bellini F, Bellwied R, Belokurova S, Bencedi G, Beole S, Bercuci A, Berdnikov Y, Berdnikova A, Bergmann L, Besoiu MG, Betev L, Bhaduri PP, Bhasin A, Bhat MA, Bhattacharjee B, Bianchi L, Bianchi N, Bielčík J, Bielčíková J, Biernat J, Bigot AP, Bilandzic A, Biro G, Biswas S, Bize N, Blair JT, Blau D, Blidaru MB, Bluhme N, Blume C, Boca G, Bock F, Bodova T, Bogdanov A, Boi S, Bok J, Boldizsár L, Bombara M, Bond PM, Bonomi G, Borel H, Borissov A, Borquez Carcamo AG, Bossi H, Botta E, Bouziani YEM, Bratrud L, Braun-Munzinger P, Bregant M, Broz M, Bruno GE, Buckland MD, Budnikov D, Buesching H, Bufalino S, Buhler P, Burmasov N, Buthelezi Z, Bylinkin A, Bysiak SA, Cai M, Caines H, Caliva A, Calvo Villar E, Camacho JMM, Camerini P, Canedo FDM, Cantway SL, Carabas M, Carballo AA, Carnesecchi F, Caron R, Carvalho LAD, Castillo Castellanos J, Catalano F, Ceballos Sanchez C, Chakaberia I, Chakraborty P, Chandra S, Chapeland S, Chartier M, Chattopadhyay S, Chattopadhyay S, Cheng T, Cheshkov C, Cheynis B, Chibante Barroso V, Chinellato DD, Chizzali ES, Cho J, Cho S, Chochula P, Christakoglou P, Christensen CH, Christiansen P, Chujo T, Ciacco M, Cicalo C, Cindolo F, Ciupek MR, Clai G, Colamaria F, Colburn JS, Colella D, Colocci M, Concas M, Conesa Balbastre G, Conesa Del Valle Z, Contin G, Contreras JG, Coquet ML, Cortese P, Cosentino MR, Costa F, Costanza S, Cot C, Crkovská J, Crochet P, Cruz-Torres R, Cui P, Dainese A, Danisch MC, Danu A, Das P, Das P, Das S, Dash AR, Dash S, De Caro A, de Cataldo G, de Cuveland J, De Falco A, De Gruttola D, De Marco N, De Martin C, De Pasquale S, Deb R, Deb S, Del Grande R, Dello Stritto L, Deng W, Dhankher P, Di Bari D, Di Mauro A, Diab B, Diaz RA, Dietel T, Ding Y, Divià R, Dixit DU, Djuvsland Ø, Dmitrieva U, Dobrin A, Dönigus B, Dubinski JM, Dubla A, Dudi S, Dupieux P, Durkac M, Dzalaiova N, Eder TM, Ehlers RJ, Eisenhut F, Ejima R, Elia D, Erazmus B, Ercolessi F, Erhardt F, Ersdal MR, Espagnon B, Eulisse G, Evans D, Evdokimov S, Fabbietti L, Faggin M, Faivre J, Fan F, Fan W, Fantoni A, Fasel M, Fecchio P, Feliciello A, Feofilov G, Fernández Téllez A, Ferrandi L, Ferrer MB, Ferrero A, Ferrero C, Ferretti A, Feuillard VJG, Filova V, Finogeev D, Fionda FM, Flor F, Flores AN, Foertsch S, Fokin I, Fokin S, Fragiacomo E, Frajna E, Fuchs U, Funicello N, Furget C, Furs A, Fusayasu T, Gaardhøje JJ, Gagliardi M, Gago AM, Gahlaut T, Galvan CD, Gangadharan DR, Ganoti P, Garabatos C, Garcia AT, García Chávez T, Garcia-Solis E, Gargiulo C, Garner K, Gasik P, Gautam A, Gay Ducati MB, Germain M, Ghimouz A, Ghosh C, Giacalone M, Giubellino P, Giubilato P, Glaenzer AMC, Glässel P, Glimos E, Goh DJQ, Gonzalez V, Gorgon M, Goswami K, Gotovac S, Grabski V, Graczykowski LK, Grecka E, Grelli A, Grigoras C, Grigoriev V, Grigoryan S, Grosa F, Grosse-Oetringhaus JF, Grosso R, Grund D, Guardiano GG, Guernane R, Guilbaud M, Gulbrandsen K, Gündem T, Gunji T, Guo W, Gupta A, Gupta R, Gupta R, Gwizdziel K, Gyulai L, Habib MK, Hadjidakis C, Haider FU, Hamagaki H, Hamdi A, Hamid M, Han Y, Hanley BG, Hannigan R, Hansen J, Haque MR, Harris JW, Harton A, Hassan H, Hatzifotiadou D, Hauer P, Havener LB, Heckel ST, Hellbär E, Helstrup H, Hemmer M, Herman T, Herrera Corral G, Herrmann F, Herrmann S, Hetland KF, Heybeck B, Hillemanns H, Hippolyte B, Hoffmann FW, Hofman B, Hohlweger B, Hong GH, Horst M, Horzyk A, Hou Y, Hristov P, Hughes C, Huhn P, Huhta LM, Humanic TJ, Hutson A, Hutter D, Ilkaev R, Ilyas H, Inaba M, Innocenti GM, Ippolitov M, Isakov A, Isidori T, Islam MS, Ivanov M, Ivanov M, Ivanov V, Iversen KE, Jablonski M, Jacak B, Jacazio N, Jacobs PM, Jadlovska S, Jadlovsky J, Jaelani S, Jahnke C, Jakubowska MJ, Janik MA, Janson T, Jercic M, Ji S, Jia S, Jimenez AAP, Jonas F, Jones DM, Jowett JM, Jung J, Jung M, Junique A, Jusko A, Kabus MJ, Kaewjai J, Kalinak P, Kalteyer AS, Kalweit A, Kaplin V, Karasu Uysal A, Karatovic D, Karavichev O, Karavicheva T, Karczmarczyk P, Karpechev E, Kebschull U, Keidel R, Keijdener DLD, Keil M, Ketzer B, Khade SS, Khan AM, Khan S, Khanzadeev A, Kharlov Y, Khatun A, Khuntia A, Kidson MB, Kileng B, Kim B, Kim C, Kim DJ, Kim EJ, Kim J, Kim JS, Kim J, Kim J, Kim M, Kim S, Kim T, Kimura K, Kirsch S, Kisel I, Kiselev S, Kisiel A, Kitowski JP, Klay JL, Klein J, Klein S, Klein-Bösing C, Kleiner M, Klemenz T, Kluge A, Knospe AG, Kobdaj C, Kollegger T, Kondratyev A, Kondratyeva N, Kondratyuk E, Konig J, Konigstorfer SA, Konopka PJ, Kornakov G, Korwieser M, Koryciak SD, Kotliarov A, Kovalenko V, Kowalski M, Kozhuharov V, Králik I, Kravčáková A, Krcal L, Krivda M, Krizek F, Krizkova Gajdosova K, Kroesen M, Krüger M, Krupova DM, Kryshen E, Kučera V, Kuhn C, Kuijer PG, Kumaoka T, Kumar D, Kumar L, Kumar N, Kumar S, Kundu S, Kurashvili P, Kurepin A, Kurepin AB, Kuryakin A, Kushpil S, Kweon MJ, Kwon Y, La Pointe SL, La Rocca P, Lakrathok A, Lamanna M, Landou AR, Langoy R, Larionov P, Laudi E, Lautner L, Lavicka R, Lea R, Lee H, Legrand I, Legras G, Lehrbach J, Lelek TM, Lemmon RC, León Monzón I, Lesch MM, Lesser ED, Lévai P, Li X, Li XL, Lien J, Lietava R, Likmeta I, Lim B, Lim SH, Lindenstruth V, Lindner A, Lippmann C, Liu A, Liu DH, Liu J, Liveraro GSS, Lofnes IM, Loizides C, Lokos S, Lomker J, Loncar P, Lopez JA, Lopez X, López Torres E, Lu P, Luhder JR, Lunardon M, Luparello G, Ma YG, Mager M, Maire A, Majerz EM, Makariev MV, Malaev M, Malfattore G, Malik NM, Malik QW, Malik SK, Malinina L, Mallick D, Mallick N, Mandaglio G, Mandal SK, Manko V, Manso F, Manzari V, Mao Y, Marcjan RW, Margagliotti GV, Margotti A, Marín A, Markert C, Martinengo P, Martínez MI, Martínez García G, Martins MPP, Masciocchi S, Masera M, Masoni A, Massacrier L, Mastroserio A, Matonoha O, Mattiazzo S, Matuoka PFT, Matyja A, Mayer C, Mazuecos AL, Mazzaschi F, Mazzilli M, Mdhluli JE, Mechler AF, Melikyan Y, Menchaca-Rocha A, Meninno E, Menon AS, Meres M, Mhlanga S, Miake Y, Micheletti L, Migliorin LC, Mihaylov DL, Mikhaylov K, Mishra AN, Miśkowiec D, Modak A, Mohanty AP, Mohanty B, Mohisin Khan M, Molander MA, Monira S, Moravcova Z, Mordasini C, Moreira De Godoy DA, Morozov I, Morsch A, Mrnjavac T, Muccifora V, Muhuri S, Mulligan JD, Mulliri A, Munhoz MG, Munzer RH, Murakami H, Murray S, Musa L, Musinsky J, Myrcha JW, Naik B, Nambrath AI, Nandi BK, Nania R, Nappi E, Nassirpour AF, Nath A, Nattrass C, Naydenov MN, Neagu A, Negru A, Nellen L, Nepeivoda R, Nese S, Neskovic G, Nielsen BS, Nielsen EG, Nikolaev S, Nikulin S, Nikulin V, Noferini F, Noh S, Nomokonov P, Norman J, Novitzky N, Nowakowski P, Nyanin A, Nystrand J, Ogino M, Oh S, Ohlson A, Okorokov VA, Oleniacz J, Oliveira Da Silva AC, Oliver MH, Onnerstad A, Oppedisano C, Ortiz Velasquez A, Otwinowski J, Oya M, Oyama K, Pachmayer Y, Padhan S, Pagano D, Paić G, Paisano-Guzmán S, Palasciano A, Panebianco S, Park H, Park H, Park J, Parkkila JE, Patley Y, Patra RN, Paul B, Pei H, Peitzmann T, Peng X, Pennisi M, Peresunko D, Perez GM, Pestov Y, Petrov V, Petrovici M, Pezzi RP, Piano S, Pikna M, Pillot P, Pinazza O, Pinsky L, Pinto C, Pisano S, Płoskoń M, Planinic M, Pliquett F, Poghosyan MG, Polichtchouk B, Politano S, Poljak N, Pop A, Porteboeuf-Houssais S, Pozdniakov V, Pozos IY, Pradhan KK, Prasad SK, Prasad S, Preghenella R, Prino F, Pruneau CA, Pshenichnov I, Puccio M, Pucillo S, Pugelova Z, Qiu S, Quaglia L, Quishpe RE, Ragoni S, Rakotozafindrabe A, Ramello L, Rami F, Rancien TA, Rasa M, Räsänen SS, Rath R, Rauch MP, Ravasenga I, Read KF, Reckziegel C, Redelbach AR, Redlich K, Reetz CA, Regules-Medel HD, Rehman A, Reidt F, Reme-Ness HA, Rescakova Z, Reygers K, Riabov A, Riabov V, Ricci R, Richter M, Riedel AA, Riegler W, Ristea C, Rodriguez MV, Rodríguez Cahuantzi M, Rodríguez Ramírez SA, Røed K, Rogalev R, Rogochaya E, Rogoschinski TS, Rohr D, Röhrich D, Rojas PF, Rojas Torres S, Rokita PS, Romanenko G, Ronchetti F, Rosano A, Rosas ED, Roslon K, Rossi A, Roy A, Roy S, Rubini N, Ruggiano D, Rui R, Russek PG, Russo R, Rustamov A, Ryabinkin E, Ryabov Y, Rybicki A, Rytkonen H, Ryu J, Rzesa W, Saarimaki OAM, Sadek R, Sadhu S, Sadovsky S, Saetre J, Šafařík K, Saha P, Saha SK, Saha S, Sahoo B, Sahoo B, Sahoo R, Sahoo S, Sahu D, Sahu PK, Saini J, Sajdakova K, Sakai S, Salvan MP, Sambyal S, Sanna I, Saramela TB, Sarkar D, Sarkar N, Sarma P, Sarritzu V, Sarti VM, Sas MHP, Schambach J, Scheid HS, Schiaua C, Schicker R, Schmah A, Schmidt C, Schmidt HR, Schmidt MO, Schmidt M, Schmidt NV, Schmier AR, Schotter R, Schröter A, Schukraft J, Schweda K, Scioli G, Scomparin E, Seger JE, Sekiguchi Y, Sekihata D, Selina M, Selyuzhenkov I, Senyukov S, Seo JJ, Serebryakov D, Šerkšnytė L, Sevcenco A, Shaba TJ, Shabetai A, Shahoyan R, Shangaraev A, Sharma A, Sharma B, Sharma D, Sharma H, Sharma M, Sharma S, Sharma S, Sharma U, Shatat A, Sheibani O, Shigaki K, Shimomura M, Shin J, Shirinkin S, Shou Q, Sibiriak Y, Siddhanta S, Siemiarczuk T, Silva TF, Silvermyr D, Simantathammakul T, Simeonov R, Singh B, Singh B, Singh K, Singh R, Singh R, Singh R, Singh S, Singh VK, Singhal V, Sinha T, Sitar B, Sitta M, Skaali TB, Skorodumovs G, Slupecki M, Smirnov N, Snellings RJM, Solheim EH, Song J, Songmoolnak A, Sonnabend C, Soramel F, Soto-Hernandez AB, Spijkers R, Sputowska I, Staa J, Stachel J, Stan I, Steffanic PJ, Stiefelmaier SF, Stocco D, Storehaug I, Stratmann P, Strazzi S, Stylianidis CP, Suaide AAP, Suire C, Sukhanov M, Suljic M, Sultanov R, Sumberia V, Sumowidagdo S, Swain S, Szarka I, Szymkowski M, Taghavi SF, Taillepied G, Takahashi J, Tambave GJ, Tang S, Tang Z, Tapia Takaki JD, Tapus N, Tarasovicova LA, Tarzila MG, Tassielli GF, Tauro A, Tejeda Muñoz G, Telesca A, Terlizzi L, Terrevoli C, Thakur S, Thomas D, Tikhonov A, Timmins AR, Tkacik M, Tkacik T, Toia A, Tokumoto R, Tomohiro K, Topilskaya N, Toppi M, Tork T, Torres VV, Torres Ramos AG, Trifiró A, Triolo AS, Tripathy S, Tripathy T, Trogolo S, Trubnikov V, Trzaska WH, Trzcinski TP, Tumkin A, Turrisi R, Tveter TS, Ullaland K, Ulukutlu B, Uras A, Urioni M, Usai GL, Vala M, Valle N, van Doremalen LVR, van Leeuwen M, van Veen CA, van Weelden RJG, Vande Vyvre P, Varga D, Varga Z, Vasileiou M, Vasiliev A, Vázquez Doce O, Vazquez Rueda O, Vechernin V, Vercellin E, Vergara Limón S, Verma R, Vermunt L, Vértesi R, Verweij M, Vickovic L, Vilakazi Z, Villalobos Baillie O, Villani A, Vino G, Vinogradov A, Virgili T, Virta MMO, Vislavicius V, Vodopyanov A, Volkel B, Völkl MA, Voloshin K, Voloshin SA, Volpe G, von Haller B, Vorobyev I, Vozniuk N, Vrláková J, Wan J, Wang C, Wang D, Wang Y, Wang Y, Wegrzynek A, Weiglhofer FT, Wenzel SC, Wessels JP, Wiechula J, Wikne J, Wilk G, Wilkinson J, Willems GA, Windelband B, Winn M, Wright JR, Wu W, Wu Y, Xu R, Yadav A, Yadav AK, Yalcin S, Yamaguchi Y, Yang S, Yano S, Yin Z, Yoo IK, Yoon JH, Yu H, Yuan S, Yuncu A, Zaccolo V, Zampolli C, Zanone F, Zardoshti N, Zarochentsev A, Závada P, Zaviyalov N, Zhalov M, Zhang B, Zhang C, Zhang L, Zhang S, Zhang X, Zhang Y, Zhang Z, Zhao M, Zherebchevskii V, Zhi Y, Zhou D, Zhou Y, Zhu J, Zhu Y, Zugravel SC, Zurlo N. First Measurement of the |t| Dependence of Incoherent J/ψ Photonuclear Production. PHYSICAL REVIEW LETTERS 2024; 132:162302. [PMID: 38701458 DOI: 10.1103/physrevlett.132.162302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 11/22/2023] [Accepted: 01/23/2024] [Indexed: 05/05/2024]
Abstract
The first measurement of the cross section for incoherent photonuclear production of J/ψ vector mesons as a function of the Mandelstam |t| variable is presented. The measurement was carried out with the ALICE detector at midrapidity, |y|<0.8, using ultraperipheral collisions of Pb nuclei at a center-of-mass energy per nucleon pair of sqrt[s_{NN}]=5.02 TeV. This rapidity interval corresponds to a Bjorken-x range (0.3-1.4)×10^{-3}. Cross sections are given in five |t| intervals in the range 0.04<|t|<1 GeV^{2} and compared to the predictions by different models. Models that ignore quantum fluctuations of the gluon density in the colliding hadron predict a |t| dependence of the cross section much steeper than in data. The inclusion of such fluctuations in the same models provides a better description of the data.
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Yoon J, Yang J, Lee HS, Kim MJ, Park VY, Rho M, Yoon JH. AI analytics can be used as imaging biomarkers for predicting invasive upgrade of ductal carcinoma in situ. Insights Imaging 2024; 15:100. [PMID: 38578585 PMCID: PMC10997564 DOI: 10.1186/s13244-024-01673-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Accepted: 03/11/2024] [Indexed: 04/06/2024] Open
Abstract
OBJECTIVES To evaluate whether the quantitative abnormality scores provided by artificial intelligence (AI)-based computer-aided detection/diagnosis (CAD) for mammography interpretation can be used to predict invasive upgrade in ductal carcinoma in situ (DCIS) diagnosed on percutaneous biopsy. METHODS Four hundred forty DCIS in 420 women (mean age, 52.8 years) diagnosed via percutaneous biopsy from January 2015 to December 2019 were included. Mammographic characteristics were assessed based on imaging features (mammographically occult, mass/asymmetry/distortion, calcifications only, and combined mass/asymmetry/distortion with calcifications) and BI-RADS assessments. Routine pre-biopsy 4-view digital mammograms were analyzed using AI-CAD to obtain abnormality scores (AI-CAD score, ranging 0-100%). Multivariable logistic regression was performed to identify independent predictive mammographic variables after adjusting for clinicopathological variables. A subgroup analysis was performed with mammographically detected DCIS. RESULTS Of the 440 DCIS, 117 (26.6%) were upgraded to invasive cancer. Three hundred forty-one (77.5%) DCIS were detected on mammography. The multivariable analysis showed that combined features (odds ratio (OR): 2.225, p = 0.033), BI-RADS 4c or 5 assessments (OR: 2.473, p = 0.023 and OR: 5.190, p < 0.001, respectively), higher AI-CAD score (OR: 1.009, p = 0.007), AI-CAD score ≥ 50% (OR: 1.960, p = 0.017), and AI-CAD score ≥ 75% (OR: 2.306, p = 0.009) were independent predictors of invasive upgrade. In mammographically detected DCIS, combined features (OR: 2.194, p = 0.035), and higher AI-CAD score (OR: 1.008, p = 0.047) were significant predictors of invasive upgrade. CONCLUSION The AI-CAD score was an independent predictor of invasive upgrade for DCIS. Higher AI-CAD scores, especially in the highest quartile of ≥ 75%, can be used as an objective imaging biomarker to predict invasive upgrade in DCIS diagnosed with percutaneous biopsy. CRITICAL RELEVANCE STATEMENT Noninvasive imaging features including the quantitative results of AI-CAD for mammography interpretation were independent predictors of invasive upgrade in lesions initially diagnosed as ductal carcinoma in situ via percutaneous biopsy and therefore may help decide the direction of surgery before treatment. KEY POINTS • Predicting ductal carcinoma in situ upgrade is important, yet there is a lack of conclusive non-invasive biomarkers. • AI-CAD scores-raw numbers, ≥ 50%, and ≥ 75%-predicted ductal carcinoma in situ upgrade independently. • Quantitative AI-CAD results may help predict ductal carcinoma in situ upgrade and guide patient management.
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Acharya S, Adamová D, Adler A, Aglieri Rinella G, Agnello M, Agrawal N, Ahammed Z, Ahmad S, Ahn SU, Ahuja I, Akindinov A, Al-Turany M, Aleksandrov D, Alessandro B, Alfanda HM, Alfaro Molina R, Ali B, Alici A, Alizadehvandchali N, Alkin A, Alme J, Alocco G, Alt T, Altsybeev I, Anaam MN, Andrei C, Andronic A, Anguelov V, Antinori F, Antonioli P, Apadula N, Aphecetche L, Appelshäuser H, Arata C, Arcelli S, Aresti M, Arnaldi R, Arsene IC, Arslandok M, Augustinus A, Averbeck R, Azmi MD, Badalà A, Bae J, Baek YW, Bai X, Bailhache R, Bailung Y, Balbino A, Baldisseri A, Balis B, Banerjee D, Banoo Z, Barbera R, Barile F, Barioglio L, Barlou M, Barnaföldi GG, Barnby LS, Barret V, Barreto L, Bartels C, Barth K, Bartsch E, Baruffaldi F, Bastid N, Basu S, Batigne G, Battistini D, Batyunya B, Bauri D, Bazo Alba JL, Bearden IG, Beattie C, Becht P, Behera D, Belikov I, Bell Hechavarria ADC, Bellini F, Bellwied R, Belokurova S, Belyaev V, Bencedi G, Beole S, Bercuci A, Berdnikov Y, Berdnikova A, Bergmann L, Besoiu MG, Betev L, Bhaduri PP, Bhasin A, Bhat MA, Bhattacharjee B, Bianchi L, Bianchi N, Bielčík J, Bielčíková J, Biernat J, Bigot AP, Bilandzic A, Biro G, Biswas S, Bize N, Blair JT, Blau D, Blidaru MB, Bluhme N, Blume C, Boca G, Bock F, Bodova T, Bogdanov A, Boi S, Bok J, Boldizsár L, Bolozdynya A, Bombara M, Bond PM, Bonomi G, Borel H, Borissov A, Borquez Carcamo AG, Bossi H, Botta E, Bouziani YEM, Bratrud L, Braun-Munzinger P, Bregant M, Broz M, Bruno GE, Budnikov D, Buesching H, Bufalino S, Bugnon O, Buhler P, Buthelezi Z, Bysiak SA, Cai M, Caines H, Caliva A, Calvo Villar E, Camacho JMM, Camerini P, Canedo FDM, Carabas M, Carballo AA, Carnesecchi F, Caron R, Castillo Castellanos J, Catalano F, Ceballos Sanchez C, Chakaberia I, Chakraborty P, Chandra S, Chapeland S, Chartier M, Chattopadhyay S, Chattopadhyay S, Chavez TG, Cheng T, Cheshkov C, Cheynis B, Chibante Barroso V, Chinellato DD, Chizzali ES, Cho J, Cho S, Chochula P, Christakoglou P, Christensen CH, Christiansen P, Chujo T, Ciacco M, Cicalo C, Cindolo F, Ciupek MR, Clai G, Colamaria F, Colburn JS, Colella D, Colocci M, Concas M, Conesa Balbastre G, Conesa Del Valle Z, Contin G, Contreras JG, Coquet ML, Cormier TM, Cortese P, Cosentino MR, Costa F, Costanza S, Crkovská J, Crochet P, Cruz-Torres R, Cuautle E, Cui P, Dainese A, Danisch MC, Danu A, Das P, Das P, Das S, Dash AR, Dash S, De Caro A, de Cataldo G, de Cuveland J, De Falco A, De Gruttola D, De Marco N, De Martin C, De Pasquale S, Deb S, Debski RJ, Deja KR, Del Grande R, Dello Stritto L, Deng W, Dhankher P, Di Bari D, Di Mauro A, Diaz RA, Dietel T, Ding Y, Divià R, Dixit DU, Djuvsland Ø, Dmitrieva U, Dobrin A, Dönigus B, Dubinski JM, Dubla A, Dudi S, Dupieux P, Durkac M, Dzalaiova N, Eder TM, Ehlers RJ, Eikeland VN, Eisenhut F, Elia D, Erazmus B, Ercolessi F, Erhardt F, Ersdal MR, Espagnon B, Eulisse G, Evans D, Evdokimov S, Fabbietti L, Faggin M, Faivre J, Fan F, Fan W, Fantoni A, Fasel M, Fecchio P, Feliciello A, Feofilov G, Fernández Téllez A, Ferrandi L, Ferrer MB, Ferrero A, Ferrero C, Ferretti A, Feuillard VJG, Filova V, Finogeev D, Fionda FM, Flor F, Flores AN, Foertsch S, Fokin I, Fokin S, Fragiacomo E, Frajna E, Fuchs U, Funicello N, Furget C, Furs A, Fusayasu T, Gaardhøje JJ, Gagliardi M, Gago AM, Galvan CD, Gangadharan DR, Ganoti P, Garabatos C, Garcia JRA, Garcia-Solis E, Garg K, Gargiulo C, Garibli A, Garner K, Gasik P, Gautam A, Gay Ducati MB, Germain M, Ghosh C, Giacalone M, Giubellino P, Giubilato P, Glaenzer AMC, Glässel P, Glimos E, Goh DJQ, Gonzalez V, González-Trueba LH, Gorgon M, Gotovac S, Grabski V, Graczykowski LK, Grecka E, Grelli A, Grigoras C, Grigoriev V, Grigoryan S, Grosa F, Grosse-Oetringhaus JF, Grosso R, Grund D, Guardiano GG, Guernane R, Guilbaud M, Gulbrandsen K, Gundem T, Gunji T, Guo W, Gupta A, Gupta R, Guzman SP, Gyulai L, Habib MK, Hadjidakis C, Haider FU, Hamagaki H, Hamdi A, Hamid M, Han Y, Hannigan R, Haque MR, Harris JW, Harton A, Hassan H, Hatzifotiadou D, Hauer P, Havener LB, Heckel ST, Hellbär E, Helstrup H, Hemmer M, Herman T, Herrera Corral G, Herrmann F, Herrmann S, Hetland KF, Heybeck B, Hillemanns H, Hills C, Hippolyte B, Hofman B, Hohlweger B, Hong GH, Horst M, Horzyk A, Hosokawa R, Hou Y, Hristov P, Hughes C, Huhn P, Huhta LM, Hulse CV, Humanic TJ, Hushnud H, Hutson A, Hutter D, Iddon JP, Ilkaev R, Ilyas H, Inaba M, Innocenti GM, Ippolitov M, Isakov A, Isidori T, Islam MS, Ivanov M, Ivanov M, Ivanov V, Jablonski M, Jacak B, Jacazio N, Jacobs PM, Jadlovska S, Jadlovsky J, Jaelani S, Jaffe L, Jahnke C, Jakubowska MJ, Janik MA, Janson T, Jercic M, Jia S, Jimenez AAP, Jonas F, Jowett JM, Jung J, Jung M, Junique A, Jusko A, Kabus MJ, Kaewjai J, Kalinak P, Kalteyer AS, Kalweit A, Kaplin V, Karasu Uysal A, Karatovic D, Karavichev O, Karavicheva T, Karczmarczyk P, Karpechev E, Kebschull U, Keidel R, Keijdener DLD, Keil M, Ketzer B, Khan AM, Khan S, Khanzadeev A, Kharlov Y, Khatun A, Khuntia A, Kidson MB, Kileng B, Kim B, Kim C, Kim DJ, Kim EJ, Kim J, Kim JS, Kim J, Kim J, Kim M, Kim S, Kim T, Kimura K, Kirsch S, Kisel I, Kiselev S, Kisiel A, Kitowski JP, Klay JL, Klein J, Klein S, Klein-Bösing C, Kleiner M, Klemenz T, Kluge A, Knospe AG, Kobdaj C, Kollegger T, Kondratyev A, Kondratyuk E, Konig J, Konigstorfer SA, Konopka PJ, Kornakov G, Koryciak SD, Kotliarov A, Kovalenko V, Kowalski M, Kozhuharov V, Králik I, Kravčáková A, Kreis L, Krivda M, Krizek F, Krizkova Gajdosova K, Kroesen M, Krüger M, Krupova DM, Kryshen E, Kučera V, Kuhn C, Kuijer PG, Kumaoka T, Kumar D, Kumar L, Kumar N, Kumar S, Kundu S, Kurashvili P, Kurepin A, Kurepin AB, Kuryakin A, Kushpil S, Kvapil J, Kweon MJ, Kwon JY, Kwon Y, La Pointe SL, La Rocca P, Lai YS, Lakrathok A, Lamanna M, Langoy R, Larionov P, Laudi E, Lautner L, Lavicka R, Lazareva T, Lea R, Lee H, Legras G, Lehrbach J, Lemmon RC, León Monzón I, Lesch MM, Lesser ED, Lettrich M, Lévai P, Li X, Li XL, Lien J, Lietava R, Lim B, Lim SH, Lindenstruth V, Lindner A, Lippmann C, Liu A, Liu DH, Liu J, Lofnes IM, Loizides C, Lokos S, Loncar P, Lopez JA, Lopez X, López Torres E, Lu P, Luhder JR, Lunardon M, Luparello G, Ma YG, Maevskaya A, Mager M, Mahmoud T, Maire A, Makariev MV, Malaev M, Malfattore G, Malik NM, Malik QW, Malik SK, Malinina L, Mal'Kevich D, Mallick D, Mallick N, Mandaglio G, Manko V, Manso F, Manzari V, Mao Y, Margagliotti GV, Margotti A, Marín A, Markert C, Martinengo P, Martinez JL, Martínez MI, Martínez García G, Masciocchi S, Masera M, Masoni A, Massacrier L, Mastroserio A, Mathis AM, Matonoha O, Matuoka PFT, Matyja A, Mayer C, Mazuecos AL, Mazzaschi F, Mazzilli M, Mdhluli JE, Mechler AF, Melikyan Y, Menchaca-Rocha A, Meninno E, Menon AS, Meres M, Mhlanga S, Miake Y, Micheletti L, Migliorin LC, Mihaylov DL, Mikhaylov K, Mishra AN, Miśkowiec D, Modak A, Mohanty AP, Mohanty B, Khan MM, Molander MA, Moravcova Z, Mordasini C, Moreira De Godoy DA, Morozov I, Morsch A, Mrnjavac T, Muccifora V, Muhuri S, Mulligan JD, Mulliri A, Munhoz MG, Munzer RH, Murakami H, Murray S, Musa L, Musinsky J, Myrcha JW, Naik B, Nambrath AI, Nandi BK, Nania R, Nappi E, Nassirpour AF, Nath A, Nattrass C, Naydenov MN, Neagu A, Negru A, Nellen L, Nesbo SV, Neskovic G, Nesterov D, Nielsen BS, Nielsen EG, Nikolaev S, Nikulin S, Nikulin V, Noferini F, Noh S, Nomokonov P, Norman J, Novitzky N, Nowakowski P, Nyanin A, Nystrand J, Ogino M, Ohlson A, Okorokov VA, Oleniacz J, Oliveira Da Silva AC, Oliver MH, Onnerstad A, Oppedisano C, Ortiz Velasquez A, Otwinowski J, Oya M, Oyama K, Pachmayer Y, Padhan S, Pagano D, Paić G, Palasciano A, Panebianco S, Park H, Park H, Park J, Parkkila JE, Patra RN, Paul B, Pei H, Peitzmann T, Peng X, Pennisi M, Pereira LG, Peresunko D, Perez GM, Perrin S, Pestov Y, Petráček V, Petrov V, Petrovici M, Pezzi RP, Piano S, Pikna M, Pillot P, Pinazza O, Pinsky L, Pinto C, Pisano S, Płoskoń M, Planinic M, Pliquett F, Poghosyan MG, Polichtchouk B, Politano S, Poljak N, Pop A, Porteboeuf-Houssais S, Pozdniakov V, Pradhan KK, Prasad SK, Prasad S, Preghenella R, Prino F, Pruneau CA, Pshenichnov I, Puccio M, Pucillo S, Pugelova Z, Qiu S, Quaglia L, Quishpe RE, Ragoni S, Rakotozafindrabe A, Ramello L, Rami F, Ramirez SAR, Rancien TA, Rasa M, Räsänen SS, Rath R, Rauch MP, Ravasenga I, Read KF, Reckziegel C, Redelbach AR, Redlich K, Rehman A, Reidt F, Reme-Ness HA, Rescakova Z, Reygers K, Riabov A, Riabov V, Ricci R, Richter M, Riedel AA, Riegler W, Ristea C, Rodríguez Cahuantzi M, Røed K, Rogalev R, Rogochaya E, Rogoschinski TS, Rohr D, Röhrich D, Rojas PF, Rojas Torres S, Rokita PS, Romanenko G, Ronchetti F, Rosano A, Rosas ED, Rossi A, Roy A, Roy S, Rubini N, Rueda OV, Ruggiano D, Rui R, Rumyantsev B, Russek PG, Russo R, Rustamov A, Ryabinkin E, Ryabov Y, Rybicki A, Rytkonen H, Rzesa W, Saarimaki OAM, Sadek R, Sadhu S, Sadovsky S, Saetre J, Šafařík K, Saha SK, Saha S, Sahoo B, Sahoo R, Sahoo S, Sahu D, Sahu PK, Saini J, Sajdakova K, Sakai S, Salvan MP, Sambyal S, Sanna I, Saramela TB, Sarkar D, Sarkar N, Sarma P, Sarritzu V, Sarti VM, Sas MHP, Schambach J, Scheid HS, Schiaua C, Schicker R, Schmah A, Schmidt C, Schmidt HR, Schmidt MO, Schmidt M, Schmidt NV, Schmier AR, Schotter R, Schröter A, Schukraft J, Schwarz K, Schweda K, Scioli G, Scomparin E, Seger JE, Sekiguchi Y, Sekihata D, Selyuzhenkov I, Senyukov S, Seo JJ, Serebryakov D, Šerkšnytė L, Sevcenco A, Shaba TJ, Shabetai A, Shahoyan R, Shangaraev A, Sharma A, Sharma D, Sharma H, Sharma M, Sharma S, Sharma S, Sharma U, Shatat A, Sheibani O, Shigaki K, Shimomura M, Shin J, Shirinkin S, Shou Q, Sibiriak Y, Siddhanta S, Siemiarczuk T, Silva TF, Silvermyr D, Simantathammakul T, Simeonov R, Singh B, Singh B, Singh R, Singh R, Singh R, Singh S, Singh VK, Singhal V, Sinha T, Sitar B, Sitta M, Skaali TB, Skorodumovs G, Slupecki M, Smirnov N, Snellings RJM, Solheim EH, Song J, Songmoolnak A, Soramel F, Spijkers R, Sputowska I, Staa J, Stachel J, Stan I, Steffanic PJ, Stiefelmaier SF, Stocco D, Storehaug I, Stratmann P, Strazzi S, Stylianidis CP, Suaide AAP, Suire C, Sukhanov M, Suljic M, Sultanov R, Sumberia V, Sumowidagdo S, Swain S, Szarka I, Taghavi SF, Taillepied G, Takahashi J, Tambave GJ, Tang S, Tang Z, Tapia Takaki JD, Tapus N, Tarasovicova LA, Tarzila MG, Tassielli GF, Tauro A, Tejeda Muñoz G, Telesca A, Terlizzi L, Terrevoli C, Tersimonov G, Thakur S, Thomas D, Tikhonov A, Timmins AR, Tkacik M, Tkacik T, Toia A, Tokumoto R, Topilskaya N, Toppi M, Torales-Acosta F, Tork T, Torres Ramos AG, Trifiró A, Triolo AS, Tripathy S, Tripathy T, Trogolo S, Trubnikov V, Trzaska WH, Trzcinski TP, Tumkin A, Turrisi R, Tveter TS, Ullaland K, Ulukutlu B, Uras A, Urioni M, Usai GL, Vala M, Valle N, van Doremalen LVR, van Leeuwen M, van Veen CA, van Weelden RJG, Vande Vyvre P, Varga D, Varga Z, Vasileiou M, Vasiliev A, Vázquez Doce O, Vechernin V, Vercellin E, Vergara Limón S, Vermunt L, Vértesi R, Verweij M, Vickovic L, Vilakazi Z, Villalobos Baillie O, Vino G, Vinogradov A, Virgili T, Vislavicius V, Vodopyanov A, Volkel B, Völkl MA, Voloshin K, Voloshin SA, Volpe G, von Haller B, Vorobyev I, Vozniuk N, Vrláková J, Wang C, Wang D, Wang Y, Wegrzynek A, Weiglhofer FT, Wenzel SC, Wessels JP, Weyhmiller SL, Wiechula J, Wikne J, Wilk G, Wilkinson J, Willems GA, Windelband B, Winn M, Wright JR, Wu W, Wu Y, Xu R, Yadav A, Yadav AK, Yalcin S, Yamaguchi Y, Yamakawa K, Yang S, Yano S, Yin Z, Yoo IK, Yoon JH, Yuan S, Yuncu A, Zaccolo V, Zampolli C, Zanone F, Zardoshti N, Zarochentsev A, Závada P, Zaviyalov N, Zhalov M, Zhang B, Zhang L, Zhang S, Zhang X, Zhang Y, Zhang Z, Zhao M, Zherebchevskii V, Zhi Y, Zhou D, Zhou Y, Zhu J, Zhu Y, Zugravel SC, Zurlo N. ψ(2S) Suppression in Pb-Pb Collisions at the LHC. PHYSICAL REVIEW LETTERS 2024; 132:042301. [PMID: 38335364 DOI: 10.1103/physrevlett.132.042301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 05/25/2023] [Accepted: 11/20/2023] [Indexed: 02/12/2024]
Abstract
The production of the ψ(2S) charmonium state was measured with ALICE in Pb-Pb collisions at sqrt[s_{NN}]=5.02 TeV, in the dimuon decay channel. A significant signal was observed for the first time at LHC energies down to zero transverse momentum, at forward rapidity (2.5
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Lee SE, Yoon JH, Son NH, Han K, Moon HJ. Screening in Patients With Dense Breasts: Comparison of Mammography, Artificial Intelligence, and Supplementary Ultrasound. AJR Am J Roentgenol 2024; 222:e2329655. [PMID: 37493324 DOI: 10.2214/ajr.23.29655] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/27/2023]
Abstract
BACKGROUND. Screening mammography has decreased performance in patients with dense breasts. Supplementary screening ultrasound is a recommended option in such patients, although it has yielded mixed results in prior investigations. OBJECTIVE. The purpose of this article is to compare the performance characteristics of screening mammography alone, standalone artificial intelligence (AI), ultrasound alone, and mammography in combination with AI and/or ultrasound in patients with dense breasts. METHODS. This retrospective study included 1325 women (mean age, 53 years) with dense breasts who underwent both screening mammography and supplementary breast ultrasound within a 1-month interval from January 2017 to December 2017; prior mammography and prior ultrasound examinations were available for comparison in 91.2% and 91.8%, respectively. Mammography and ultrasound examinations were interpreted by one of 15 radiologists (five staff; 10 fellows); clinical reports were used for the present analysis. A commercial AI tool was used to retrospectively evaluate mammographic examinations for presence of cancer. Screening performances were compared among mammography, AI, ultrasound, and test combinations, using generalized estimating equations. Benign diagnoses required 24 months or longer of imaging stability. RESULTS. Twelve cancers (six invasive ductal carcinoma; six ductal carcinoma in situ) were diagnosed. Mammography, standalone AI, and ultrasound showed cancer detection rates (per 1000 patients) of 6.0, 6.8, and 6.0 (all p > .05); recall rates of 4.4%, 11.9%, and 9.2% (all p < .05); sensitivity of 66.7%, 75.0%, and 66.7% (all p > .05); specificity of 96.2%, 88.7%, and 91.3% (all p < .05); and accuracy of 95.9%, 88.5%, and 91.1% (all p < .05). Mammography with AI, mammography with ultrasound, and mammography with both ultrasound and AI showed cancer detection rates of 7.5, 9.1, and 9.1 (all p > .05); recall rates of 14.9, 11.7, and 21.4 (all p < .05); sensitivity of 83.3%, 100.0%, and 100.0% (all p > .05); specificity of 85.8%, 89.1%, and 79.4% (all p < .05); and accuracy of 85.7%, 89.2%, and 79.5% (all p < .05). CONCLUSION. Mammography with supplementary ultrasound showed higher accuracy, higher specificity, and lower recall rate in comparison with mammography with AI and in comparison with mammography with both ultrasound and AI. CLINICAL IMPACT. The findings fail to show benefit of AI with respect to screening mammography performed with supplementary breast ultrasound in patients with dense breasts.
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Kim YS, Lee SH, Kim SY, Kim ES, Park AR, Chang JM, Park VY, Yoon JH, Kang BJ, Yun BL, Kim TH, Ko ES, Chu AJ, Kim JY, Youn I, Chae EY, Choi WJ, Kim HJ, Kang SH, Ha SM, Moon WK. Unenhanced Breast MRI With Diffusion-Weighted Imaging for Breast Cancer Detection: Effects of Training on Performance and Agreement of Subspecialty Radiologists. Korean J Radiol 2024; 25:11-23. [PMID: 38184765 PMCID: PMC10788600 DOI: 10.3348/kjr.2023.0528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2023] [Revised: 10/26/2023] [Accepted: 10/30/2023] [Indexed: 01/08/2024] Open
Abstract
OBJECTIVE To investigate whether reader training improves the performance and agreement of radiologists in interpreting unenhanced breast magnetic resonance imaging (MRI) scans using diffusion-weighted imaging (DWI). MATERIALS AND METHODS A study of 96 breasts (35 cancers, 24 benign, and 37 negative) in 48 asymptomatic women was performed between June 2019 and October 2020. High-resolution DWI with b-values of 0, 800, and 1200 sec/mm² was performed using a 3.0-T system. Sixteen breast radiologists independently reviewed the DWI, apparent diffusion coefficient maps, and T1-weighted MRI scans and recorded the Breast Imaging Reporting and Data System (BI-RADS) category for each breast. After a 2-h training session and a 5-month washout period, they re-evaluated the BI-RADS categories. A BI-RADS category of 4 (lesions with at least two suspicious criteria) or 5 (more than two suspicious criteria) was considered positive. The per-breast diagnostic performance of each reader was compared between the first and second reviews. Inter-reader agreement was evaluated using a multi-rater κ analysis and intraclass correlation coefficient (ICC). RESULTS Before training, the mean sensitivity, specificity, and accuracy of the 16 readers were 70.7% (95% confidence interval [CI]: 59.4-79.9), 90.8% (95% CI: 85.6-94.2), and 83.5% (95% CI: 78.6-87.4), respectively. After training, significant improvements in specificity (95.2%; 95% CI: 90.8-97.5; P = 0.001) and accuracy (85.9%; 95% CI: 80.9-89.8; P = 0.01) were observed, but no difference in sensitivity (69.8%; 95% CI: 58.1-79.4; P = 0.58) was observed. Regarding inter-reader agreement, the κ values were 0.57 (95% CI: 0.52-0.63) before training and 0.68 (95% CI: 0.62-0.74) after training, with a difference of 0.11 (95% CI: 0.02-0.18; P = 0.01). The ICC was 0.73 (95% CI: 0.69-0.74) before training and 0.79 (95% CI: 0.76-0.80) after training (P = 0.002). CONCLUSION Brief reader training improved the performance and agreement of interpretations by breast radiologists using unenhanced MRI with DWI.
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Yoon JH, Han K, Suh HJ, Youk JH, Lee SE, Kim EK. Artificial intelligence-based computer-assisted detection/diagnosis (AI-CAD) for screening mammography: Outcomes of AI-CAD in the mammographic interpretation workflow. Eur J Radiol Open 2023; 11:100509. [PMID: 37484980 PMCID: PMC10362167 DOI: 10.1016/j.ejro.2023.100509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2023] [Revised: 07/03/2023] [Accepted: 07/09/2023] [Indexed: 07/25/2023] Open
Abstract
Purpose To evaluate the stand-alone diagnostic performances of AI-CAD and outcomes of AI-CAD detected abnormalities when applied to the mammographic interpretation workflow. Methods From January 2016 to December 2017, 6499 screening mammograms of 5228 women were collected from a single screening facility. Historic reads of three radiologists were used as radiologist interpretation. A commercially-available AI-CAD was used for analysis. One radiologist not involved in interpretation had retrospectively reviewed the abnormality features and assessed the significance (negligible vs. need recall) of the AI-CAD marks. Ground truth in terms of cancer, benign or absence of abnormality was confirmed according to histopathologic diagnosis or negative results on the next-round screen. Results Of the 6499 mammograms, 6282 (96.7%) were in the negative, 189 (2.9%) were in the benign, and 28 (0.4%) were in the cancer group. AI-CAD detected 5 (17.9%, 5 of 28) of the 9 cancers that were intially interpreted as negative. Of the 648 AI-CAD recalls, 89.0% (577 of 648) were marks seen on examinations in the negative group, and 267 (41.2%) of the AI-CAD marks were considered to be negligible. Stand-alone AI-CAD has significantly higher recall rates (10.0% vs. 3.4%, P < 0.001) with comparable sensitivity and cancer detection rates (P = 0.086 and 0.102, respectively) when compared to the radiologists' interpretation. Conclusion AI-CAD detected 17.9% additional cancers on screening mammography that were initially overlooked by the radiologists. In spite of the additional cancer detection, AI-CAD had significantly higher recall rates in the clinical workflow, in which 89.0% of AI-CAD marks are on negative mammograms.
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Yoon J, Lee E, Lee HS, Cho S, Son J, Kwon H, Yoon JH, Park VY, Lee M, Rho M, Kim D, Kwak JY. Learnability of Thyroid Nodule Assessment on Ultrasonography: Using a Big Data Set. ULTRASOUND IN MEDICINE & BIOLOGY 2023; 49:2581-2589. [PMID: 37758528 DOI: 10.1016/j.ultrasmedbio.2023.08.026] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 08/29/2023] [Accepted: 08/31/2023] [Indexed: 09/29/2023]
Abstract
OBJECTIVE The aims of the work described here were to evaluate the learnability of thyroid nodule assessment on ultrasonography (US) using a big data set of US images and to evaluate the diagnostic utilities of artificial intelligence computer-aided diagnosis (AI-CAD) used by readers with varying experience to differentiate benign and malignant thyroid nodules. METHODS Six college freshmen independently studied the "learning set" composed of images of 13,560 thyroid nodules, and their diagnostic performance was evaluated after their daily learning sessions using the "test set" composed of images of 282 thyroid nodules. The diagnostic performance of two residents and an experienced radiologist was evaluated using the same "test set." After an initial diagnosis, all readers once again evaluated the "test set" with the assistance of AI-CAD. RESULTS Diagnostic performance of almost all students increased after the learning program. Although the mean areas under the receiver operating characteristic curves (AUROCs) of residents and the experienced radiologist were significantly higher than those of students, the AUROCs of five of the six students did not differ significantly compared with that of the one resident. With the assistance of AI-CAD, sensitivity significantly increased in three students, specificity in one student, accuracy in four students and AUROC in four students. Diagnostic performance of the two residents and the experienced radiologist was better with the assistance of AI-CAD. CONCLUSION A self-learning method using a big data set of US images has potential as an ancillary tool alongside traditional training methods. With the assistance of AI-CAD, the diagnostic performance of readers with varying experience in thyroid imaging could be further improved.
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Acharya S, Adamová D, Adler A, Aglieri Rinella G, Agnello M, Agrawal N, Ahammed Z, Ahmad S, Ahn SU, Ahuja I, Akindinov A, Al-Turany M, Aleksandrov D, Alessandro B, Alfanda HM, Alfaro Molina R, Ali B, Ali Y, Alici A, Alizadehvandchali N, Alkin A, Alme J, Alocco G, Alt T, Altsybeev I, Anaam MN, Andrei C, Andronic A, Anguelov V, Antinori F, Antonioli P, Anuj C, Apadula N, Aphecetche L, Appelshäuser H, Arata C, Arcelli S, Aresti M, Arnaldi R, Arsene IC, Arslandok M, Augustinus A, Averbeck R, Azmi MD, Badalà A, Baek YW, Bai X, Bailhache R, Bailung Y, Bala R, Balbino A, Baldisseri A, Balis B, Banerjee D, Banoo Z, Barbera R, Barile F, Barioglio L, Barlou M, Barnaföldi GG, Barnby LS, Barret V, Barreto L, Bartels C, Barth K, Bartsch E, Baruffaldi F, Bastid N, Basu S, Batigne G, Battistini D, Batyunya B, Bauri D, Bazo Alba JL, Bearden IG, Beattie C, Becht P, Behera D, Belikov I, Bell Hechavarria ADC, Bellini F, Bellwied R, Belokurova S, Belyaev V, Bencedi G, Beole S, Bercuci A, Berdnikov Y, Berdnikova A, Bergmann L, Besoiu MG, Betev L, Bhaduri PP, Bhasin A, Bhat MA, Bhattacharjee B, Bianchi L, Bianchi N, Bielčík J, Bielčíková J, Biernat J, Bigot AP, Bilandzic A, Biro G, Biswas S, Bize N, Blair JT, Blau D, Blidaru MB, Bluhme N, Blume C, Boca G, Bock F, Bodova T, Bogdanov A, Boi S, Bok J, Boldizsár L, Bolozdynya A, Bombara M, Bond PM, Bonomi G, Borel H, Borissov A, Bossi H, Botta E, Bouziani YEM, Bratrud L, Braun-Munzinger P, Bregant M, Broz M, Bruno GE, Buckland MD, Budnikov D, Buesching H, Bufalino S, Bugnon O, Buhler P, Buthelezi Z, Butt JB, Bysiak SA, Cai M, Caines H, Caliva A, Calvo Villar E, Camacho JMM, Camerini P, Canedo FDM, Carabas M, Carnesecchi F, Caron R, Castillo Castellanos J, Catalano F, Ceballos Sanchez C, Chakaberia I, Chakraborty P, Chandra S, Chapeland S, Chartier M, Chattopadhyay S, Chattopadhyay S, Chavez TG, Cheng T, Cheshkov C, Cheynis B, Chibante Barroso V, Chinellato DD, Chizzali ES, Cho J, Cho S, Chochula P, Christakoglou P, Christensen CH, Christiansen P, Chujo T, Ciacco M, Cicalo C, Cifarelli L, Cindolo F, Ciupek MR, Clai G, Colamaria F, Colburn JS, Colella D, Colocci M, Concas M, Conesa Balbastre G, Conesa Del Valle Z, Contin G, Contreras JG, Coquet ML, Cormier TM, Cortese P, Cosentino MR, Costa F, Costanza S, Crkovská J, Crochet P, Cruz-Torres R, Cuautle E, Cui P, Cunqueiro L, Dainese A, Danisch MC, Danu A, Das P, Das P, Das S, Dash AR, Dash S, David RMH, De Caro A, de Cataldo G, de Cuveland J, De Falco A, De Gruttola D, De Marco N, De Martin C, De Pasquale S, Deb S, Debski RJ, Deja KR, Del Grande R, Dello Stritto L, Deng W, Dhankher P, Di Bari D, Di Mauro A, Diaz RA, Dietel T, Ding Y, Divià R, Dixit DU, Djuvsland Ø, Dmitrieva U, Dobrin A, Dönigus B, Dubey AK, Dubinski JM, Dubla A, Dudi S, Dupieux P, Durkac M, Dzalaiova N, Eder TM, Ehlers RJ, Eikeland VN, Eisenhut F, Elia D, Erazmus B, Ercolessi F, Erhardt F, Ersdal MR, Espagnon B, Eulisse G, Evans D, Evdokimov S, Fabbietti L, Faggin M, Faivre J, Fan F, Fan W, Fantoni A, Fasel M, Fecchio P, Feliciello A, Feofilov G, Fernández Téllez A, Ferrer MB, Ferrero A, Ferrero C, Ferretti A, Feuillard VJG, Filova V, Finogeev D, Fionda FM, Flor F, Flores AN, Foertsch S, Fokin I, Fokin S, Fragiacomo E, Frajna E, Fuchs U, Funicello N, Furget C, Furs A, Fusayasu T, Gaardhøje JJ, Gagliardi M, Gago AM, Galvan CD, Gangadharan DR, Ganoti P, Garabatos C, Garcia JRA, Garcia-Solis E, Garg K, Gargiulo C, Garibli A, Garner K, Gautam A, Gay Ducati MB, Germain M, Ghosh C, Ghosh SK, Giacalone M, Gianotti P, Giubellino P, Giubilato P, Glaenzer AMC, Glässel P, Glimos E, Goh DJQ, Gonzalez V, González-Trueba LH, Gorgon M, Gotovac S, Grabski V, Graczykowski LK, Grecka E, Grelli A, Grigoras C, Grigoriev V, Grigoryan S, Grosa F, Grosse-Oetringhaus JF, Grosso R, Grund D, Guardiano GG, Guernane R, Guilbaud M, Gulbrandsen K, Gundem T, Gunji T, Guo W, Gupta A, Gupta R, Guzman SP, Gyulai L, Habib MK, Hadjidakis C, Hamagaki H, Hamid M, Han Y, Hannigan R, Haque MR, Harris JW, Harton A, Hassan H, Hatzifotiadou D, Hauer P, Havener LB, Heckel ST, Hellbär E, Helstrup H, Hemmer M, Herman T, Herrera Corral G, Herrmann F, Herrmann S, Hetland KF, Heybeck B, Hillemanns H, Hills C, Hippolyte B, Hofman B, Hohlweger B, Honermann J, Hong GH, Horzyk A, Hosokawa R, Hou Y, Hristov P, Hughes C, Huhn P, Huhta LM, Hulse CV, Humanic TJ, Hushnud H, Hutson A, Hutter D, Iddon JP, Ilkaev R, Ilyas H, Inaba M, Innocenti GM, Ippolitov M, Isakov A, Isidori T, Islam MS, Ivanov M, Ivanov M, Ivanov V, Izucheev V, Jablonski M, Jacak B, Jacazio N, Jacobs PM, Jadlovska S, Jadlovsky J, Jaelani S, Jaffe L, Jahnke C, Jakubowska MJ, Janik MA, Janson T, Jercic M, Jevons O, Jimenez AAP, Jonas F, Jones PG, Jowett JM, Jung J, Jung M, Junique A, Jusko A, Kabus MJ, Kaewjai J, Kalinak P, Kalteyer AS, Kalweit A, Kaplin V, Karasu Uysal A, Karatovic D, Karavichev O, Karavicheva T, Karczmarczyk P, Karpechev E, Kashyap V, Kebschull U, Keidel R, Keijdener DLD, Keil M, Ketzer B, Khan AM, Khan S, Khanzadeev A, Kharlov Y, Khatun A, Khuntia A, Kileng B, Kim B, Kim C, Kim DJ, Kim EJ, Kim J, Kim JS, Kim J, Kim J, Kim M, Kim S, Kim T, Kimura K, Kirsch S, Kisel I, Kiselev S, Kisiel A, Kitowski JP, Klay JL, Klein J, Klein S, Klein-Bösing C, Kleiner M, Klemenz T, Kluge A, Knospe AG, Kobdaj C, Kollegger T, Kondratyev A, Kondratyuk E, Konig J, Konigstorfer SA, Konopka PJ, Kornakov G, Koryciak SD, Kotliarov A, Kovalenko O, Kovalenko V, Kowalski M, Králik I, Kravčáková A, Kreis L, Krivda M, Krizek F, Krizkova Gajdosova K, Kroesen M, Krüger M, Krupova DM, Kryshen E, Kučera V, Kuhn C, Kuijer PG, Kumaoka T, Kumar D, Kumar L, Kumar N, Kumar S, Kundu S, Kurashvili P, Kurepin A, Kurepin AB, Kushpil S, Kvapil J, Kweon MJ, Kwon JY, Kwon Y, La Pointe SL, La Rocca P, Lai YS, Lakrathok A, Lamanna M, Langoy R, Larionov P, Laudi E, Lautner L, Lavicka R, Lazareva T, Lea R, Legras G, Lehrbach J, Lemmon RC, León Monzón I, Lesch MM, Lesser ED, Lettrich M, Lévai P, Li X, Li XL, Lien J, Lietava R, Lim B, Lim SH, Lindenstruth V, Lindner A, Lippmann C, Liu A, Liu DH, Liu J, Lofnes IM, Loizides C, Loncar P, Lopez JA, Lopez X, López Torres E, Lu P, Luhder JR, Lunardon M, Luparello G, Ma YG, Maevskaya A, Mager M, Mahmoud T, Maire A, Malaev M, Malfattore G, Malik NM, Malik QW, Malik SK, Malinina L, Mal'Kevich D, Mallick D, Mallick N, Mandaglio G, Manko V, Manso F, Manzari V, Mao Y, Margagliotti GV, Margotti A, Marín A, Markert C, Martinengo P, Martinez JL, Martínez MI, Martínez García G, Masciocchi S, Masera M, Masoni A, Massacrier L, Mastroserio A, Mathis AM, Matonoha O, Matuoka PFT, Matyja A, Mayer C, Mazuecos AL, Mazzaschi F, Mazzilli M, Mdhluli JE, Mechler AF, Melikyan Y, Menchaca-Rocha A, Meninno E, Menon AS, Meres M, Mhlanga S, Miake Y, Micheletti L, Migliorin LC, Mihaylov DL, Mikhaylov K, Mishra AN, Miśkowiec D, Modak A, Mohanty AP, Mohanty B, Khan MM, Molander MA, Moravcova Z, Mordasini C, Moreira De Godoy DA, Morozov I, Morsch A, Mrnjavac T, Muccifora V, Muhuri S, Mulligan JD, Mulliri A, Munhoz MG, Munzer RH, Murakami H, Murray S, Musa L, Musinsky J, Myrcha JW, Naik B, Nair R, Nambrath AI, Nandi BK, Nania R, Nappi E, Nassirpour AF, Nath A, Nattrass C, Neagu A, Negru A, Nellen L, Nesbo SV, Neskovic G, Nesterov D, Nielsen BS, Nielsen EG, Nikolaev S, Nikulin S, Nikulin V, Noferini F, Noh S, Nomokonov P, Norman J, Novitzky N, Nowakowski P, Nyanin A, Nystrand J, Ogino M, Ohlson A, Okorokov VA, Oleniacz J, Oliveira Da Silva AC, Oliver MH, Onnerstad A, Oppedisano C, Ortiz Velasquez A, Oskarsson A, Otwinowski J, Oya M, Oyama K, Pachmayer Y, Padhan S, Pagano D, Paić G, Palasciano A, Panebianco S, Park H, Park J, Parkkila JE, Patra RN, Paul B, Pei H, Peitzmann T, Peng X, Pennisi M, Pereira LG, Pereira Da Costa H, Peresunko D, Perez GM, Perrin S, Pestov Y, Petráček V, Petrov V, Petrovici M, Pezzi RP, Piano S, Pikna M, Pillot P, Pinazza O, Pinsky L, Pinto C, Pisano S, Płoskoń M, Planinic M, Pliquett F, Poghosyan MG, Politano S, Poljak N, Pop A, Porteboeuf-Houssais S, Porter J, Pozdniakov V, Prasad SK, Prasad S, Preghenella R, Prino F, Pruneau CA, Pshenichnov I, Puccio M, Pucillo S, Pugelova Z, Qiu S, Quaglia L, Quishpe RE, Ragoni S, Rakotozafindrabe A, Ramello L, Rami F, Ramirez SAR, Rancien TA, Raniwala R, Raniwala S, Rasa M, Räsänen SS, Rath R, Ravasenga I, Read KF, Reckziegel C, Redelbach AR, Redlich K, Rehman A, Reidt F, Reme-Ness HA, Rescakova Z, Reygers K, Riabov A, Riabov V, Ricci R, Richert T, Richter M, Riedel AA, Riegler W, Riggi F, Ristea C, Rodríguez Cahuantzi M, Røed K, Rogalev R, Rogochaya E, Rogoschinski TS, Rohr D, Röhrich D, Rojas PF, Rojas Torres S, Rokita PS, Romanenko G, Ronchetti F, Rosano A, Rosas ED, Rossi A, Roy A, Roy P, Roy S, Rubini N, Rueda OV, Ruggiano D, Rui R, Rumyantsev B, Russek PG, Russo R, Rustamov A, Ryabinkin E, Ryabov Y, Rybicki A, Rytkonen H, Rzesa W, Saarimaki OAM, Sadek R, Sadhu S, Sadovsky S, Saetre J, Šafařík K, Saha SK, Saha S, Sahoo B, Sahoo R, Sahoo S, Sahu D, Sahu PK, Saini J, Sajdakova K, Sakai S, Salvan MP, Sambyal S, Saramela TB, Sarkar D, Sarkar N, Sarma P, Sarritzu V, Sarti VM, Sas MHP, Schambach J, Scheid HS, Schiaua C, Schicker R, Schmah A, Schmidt C, Schmidt HR, Schmidt MO, Schmidt M, Schmidt NV, Schmier AR, Schotter R, Schukraft J, Schwarz K, Schweda K, Scioli G, Scomparin E, Seger JE, Sekiguchi Y, Sekihata D, Selyuzhenkov I, Senyukov S, Seo JJ, Serebryakov D, Šerkšnytė L, Sevcenco A, Shaba TJ, Shabetai A, Shahoyan R, Shangaraev A, Sharma A, Sharma D, Sharma H, Sharma M, Sharma N, Sharma S, Sharma S, Sharma U, Shatat A, Sheibani O, Shigaki K, Shimomura M, Shirinkin S, Shou Q, Sibiriak Y, Siddhanta S, Siemiarczuk T, Silva TF, Silvermyr D, Simantathammakul T, Simeonov R, Singh B, Singh B, Singh R, Singh R, Singh R, Singh S, Singh VK, Singhal V, Sinha T, Sitar B, Sitta M, Skaali TB, Skorodumovs G, Slupecki M, Smirnov N, Snellings RJM, Solheim EH, Song J, Songmoolnak A, Soramel F, Sorensen S, Spijkers R, Sputowska I, Staa J, Stachel J, Stan I, Steffanic PJ, Stiefelmaier SF, Stocco D, Storehaug I, Storetvedt MM, Stratmann P, Strazzi S, Stylianidis CP, Suaide AAP, Suire C, Sukhanov M, Suljic M, Sumberia V, Sumowidagdo S, Swain S, Szarka I, Tabassam U, Taghavi SF, Taillepied G, Takahashi J, Tambave GJ, Tang S, Tang Z, Tapia Takaki JD, Tapus N, Tarasovicova LA, Tarzila MG, Tassielli GF, Tauro A, Telesca A, Terlizzi L, Terrevoli C, Tersimonov G, Thakur S, Thomas D, Tikhonov A, Timmins AR, Tkacik M, Tkacik T, Toia A, Tokumoto R, Topilskaya N, Toppi M, Torales-Acosta F, Tork T, Torres Ramos AG, Trifiró A, Triolo AS, Tripathy S, Tripathy T, Trogolo S, Trubnikov V, Trzaska WH, Trzcinski TP, Turrisi R, Tveter TS, Ullaland K, Ulukutlu B, Uras A, Urioni M, Usai GL, Vala M, Valle N, Vallero S, van Doremalen LVR, van Leeuwen M, van Veen CA, van Weelden RJG, Vande Vyvre P, Varga D, Varga Z, Varga-Kofarago M, Vasileiou M, Vasiliev A, Vázquez Doce O, Vechernin V, Vercellin E, Vergara Limón S, Vermunt L, Vértesi R, Verweij M, Vickovic L, Vilakazi Z, Villalobos Baillie O, Vino G, Vinogradov A, Virgili T, Vislavicius V, Vodopyanov A, Volkel B, Völkl MA, Voloshin K, Voloshin SA, Volpe G, von Haller B, Vorobyev I, Vozniuk N, Vrláková J, Wagner B, Wang C, Wang D, Wegrzynek A, Weiglhofer FT, Wenzel SC, Wessels JP, Weyhmiller SL, Wiechula J, Wikne J, Wilk G, Wilkinson J, Willems GA, Windelband B, Winn M, Wright JR, Wu W, Wu Y, Xu R, Yadav A, Yadav AK, Yalcin S, Yamaguchi Y, Yamakawa K, Yang S, Yano S, Yin Z, Yoo IK, Yoon JH, Yuan S, Yuncu A, Zaccolo V, Zampolli C, Zanoli HJC, Zanone F, Zardoshti N, Zarochentsev A, Závada P, Zaviyalov N, Zhalov M, Zhang B, Zhang S, Zhang X, Zhang Y, Zhang Z, Zhao M, Zherebchevskii V, Zhi Y, Zhigareva N, Zhou D, Zhou Y, Zhu J, Zhu Y, Zinovjev G, Zurlo N. Measurements of Groomed-Jet Substructure of Charm Jets Tagged by D^{0} Mesons in Proton-Proton Collisions at sqrt[s]=13 TeV. PHYSICAL REVIEW LETTERS 2023; 131:192301. [PMID: 38000395 DOI: 10.1103/physrevlett.131.192301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 01/13/2023] [Accepted: 07/19/2023] [Indexed: 11/26/2023]
Abstract
Understanding the role of parton mass and Casimir color factors in the quantum chromodynamics parton shower represents an important step in characterizing the emission properties of heavy quarks. Recent experimental advances in jet substructure techniques have provided the opportunity to isolate and characterize gluon emissions from heavy quarks. In this Letter, the first direct experimental constraint on the charm-quark splitting function is presented, obtained via the measurement of the groomed shared momentum fraction of the first splitting in charm jets, tagged by a reconstructed D^{0} meson. The measurement is made in proton-proton collisions at sqrt[s]=13 TeV, in the low jet transverse-momentum interval of 15≤p_{T}^{jet ch}<30 GeV/c where the emission properties are sensitive to parton mass effects. In addition, the opening angle of the first perturbative emission of the charm quark, as well as the number of perturbative emissions it undergoes, is reported. Comparisons to measurements of an inclusive-jet sample show a steeper splitting function for charm quarks compared with gluons and light quarks. Charm quarks also undergo fewer perturbative emissions in the parton shower, with a reduced probability of large-angle emissions.
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Durante C, Hegedüs L, Na DG, Papini E, Sipos JA, Baek JH, Frasoldati A, Grani G, Grant E, Horvath E, Hoang JK, Mandel SJ, Middleton WD, Ngu R, Orloff LA, Shin JH, Trimboli P, Yoon JH, Tessler FN. International Expert Consensus on US Lexicon for Thyroid Nodules. Radiology 2023; 309:e231481. [PMID: 37906014 DOI: 10.1148/radiol.231481] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2023]
Abstract
Multiple US-based systems for risk stratification of thyroid nodules are in use worldwide. Unfortunately, the malignancy probability assigned to a nodule varies, and terms and definitions are not consistent, leading to confusion and making it challenging to compare study results and craft revisions. Consistent application of these systems is further hampered by interobserver variability in identifying the sonographic features on which they are founded. In 2018, an international multidisciplinary group of 19 physicians with expertise in thyroid sonography (termed the International Thyroid Nodule Ultrasound Working Group) was convened with the goal of developing an international system, tentatively called the International Thyroid Imaging Reporting and Data System, or I-TIRADS, in two phases: (phase I) creation of a lexicon and atlas of US descriptors of thyroid nodules and (phase II) development of a system that estimates the malignancy risk of a thyroid nodule. This article presents the methods and results of phase I. The purpose herein is to show what has been accomplished thus far, as well as generate interest in and support for this effort in the global thyroid community.
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Lee J, Yoon JH, Lee E, Lee HY, Jeong S, Park S, Jo YS, Kwak JY. Immune response and mesenchymal transition of papillary thyroid carcinoma reflected in ultrasonography features assessed by radiologists and deep learning. J Adv Res 2023:S2090-1232(23)00292-8. [PMID: 37783270 DOI: 10.1016/j.jare.2023.09.043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Revised: 09/07/2023] [Accepted: 09/29/2023] [Indexed: 10/04/2023] Open
Abstract
INTRODUCTION Ultrasonography (US) features of papillary thyroid cancers (PTCs) are used to select nodules for biopsy due to their association with tumor behavior. However, the molecular biological mechanisms that lead to the characteristic US features of PTCs are largely unknown. OBJECTIVES This study aimed to investigate the molecular biological mechanisms behind US features assessed by radiologists and three convolutional neural networks (CNN) through transcriptome analysis. METHODS Transcriptome data from 273 PTC tissue samples were generated and differentially expressed genes (DEGs) were identified according to US feature. Pathway enrichment analyses were also conducted by gene set enrichment analysis (GSEA) and ClusterProfiler according to assessments made by radiologists and three CNNs - CNN1 (ResNet50), CNN2 (ResNet101) and CNN3 (VGG16). Signature gene scores for PTCs were calculated by single-sample GSEA (ssGSEA). RESULTS Individual suspicious US features consistently suggested an upregulation of genes related to immune response and epithelial-mesenchymal transition (EMT). Likewise, PTCs assessed as positive by radiologists and three CNNs showed the coordinate enrichment of similar gene sets with abundant immune and stromal components. However, PTCs assessed as positive by radiologists had the highest number of DEGs, and those assessed as positive by CNN3 had more diverse DEGs and gene sets compared to CNN1 or CNN2. The percentage of PTCs assessed as positive or negative concordantly by radiologists and three CNNs was 85.6% (231/273) and 7.1% (3/273), respectively. CONCLUSION US features assessed by radiologists and CNNs revealed molecular biologic features and tumor microenvironment in PTCs.
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Acharya S, Adamová D, Adler A, Aglieri Rinella G, Agnello M, Agrawal N, Ahammed Z, Ahmad S, Ahn SU, Ahuja I, Akindinov A, Al-Turany M, Aleksandrov D, Alessandro B, Alfanda HM, Alfaro Molina R, Ali B, Ali Y, Alici A, Alizadehvandchali N, Alkin A, Alme J, Alocco G, Alt T, Altsybeev I, Anaam MN, Andrei C, Andronic A, Anguelov V, Antinori F, Antonioli P, Anuj C, Apadula N, Aphecetche L, Appelshäuser H, Arata C, Arcelli S, Aresti M, Arnaldi R, Arsene IC, Arslandok M, Augustinus A, Averbeck R, Azmi MD, Badalà A, Baek YW, Bai X, Bailhache R, Bailung Y, Bala R, Balbino A, Baldisseri A, Balis B, Banerjee D, Banoo Z, Barbera R, Barile F, Barioglio L, Barlou M, Barnaföldi GG, Barnby LS, Barret V, Barreto L, Bartels C, Barth K, Bartsch E, Baruffaldi F, Bastid N, Basu S, Batigne G, Battistini D, Batyunya B, Bauri D, Bazo Alba JL, Bearden IG, Beattie C, Becht P, Behera D, Belikov I, Bell Hechavarria ADC, Bellini F, Bellwied R, Belokurova S, Belyaev V, Bencedi G, Beole S, Bercuci A, Berdnikov Y, Berdnikova A, Bergmann L, Besoiu MG, Betev L, Bhaduri PP, Bhasin A, Bhat MA, Bhattacharjee B, Bianchi L, Bianchi N, Bielčík J, Bielčíková J, Biernat J, Bigot AP, Bilandzic A, Biro G, Biswas S, Bize N, Blair JT, Blau D, Blidaru MB, Bluhme N, Blume C, Boca G, Bock F, Bodova T, Bogdanov A, Boi S, Bok J, Boldizsár L, Bolozdynya A, Bombara M, Bond PM, Bonomi G, Borel H, Borissov A, Borquez Carcamo AG, Bossi H, Botta E, Bouziani YEM, Bratrud L, Braun-Munzinger P, Bregant M, Broz M, Bruno GE, Buckland MD, Budnikov D, Buesching H, Bufalino S, Bugnon O, Buhler P, Buthelezi Z, Butt JB, Bysiak SA, Cai M, Caines H, Caliva A, Calvo Villar E, Camacho JMM, Camerini P, Canedo FDM, Carabas M, Carballo AA, Carnesecchi F, Caron R, Castillo Castellanos J, Catalano F, Ceballos Sanchez C, Chakaberia I, Chakraborty P, Chandra S, Chapeland S, Chartier M, Chattopadhyay S, Chattopadhyay S, Chavez TG, Cheng T, Cheshkov C, Cheynis B, Chibante Barroso V, Chinellato DD, Chizzali ES, Cho J, Cho S, Chochula P, Christakoglou P, Christensen CH, Christiansen P, Chujo T, Ciacco M, Cicalo C, Cifarelli L, Cindolo F, Ciupek MR, Clai G, Colamaria F, Colburn JS, Colella D, Colocci M, Concas M, Conesa Balbastre G, Conesa Del Valle Z, Contin G, Contreras JG, Coquet ML, Cormier TM, Cortese P, Cosentino MR, Costa F, Costanza S, Crkovská J, Crochet P, Cruz-Torres R, Cuautle E, Cui P, Cunqueiro L, Dainese A, Danisch MC, Danu A, Das P, Das P, Das S, Dash AR, Dash S, De Caro A, de Cataldo G, de Cuveland J, De Falco A, De Gruttola D, De Marco N, De Martin C, De Pasquale S, Deb S, Debski RJ, Deja KR, Del Grande R, Dello Stritto L, Deng W, Dhankher P, Di Bari D, Di Mauro A, Diaz RA, Dietel T, Ding Y, Divià R, Dixit DU, Djuvsland Ø, Dmitrieva U, Dobrin A, Dönigus B, Dubey AK, Dubinski JM, Dubla A, Dudi S, Dupieux P, Durkac M, Dzalaiova N, Eder TM, Ehlers RJ, Eikeland VN, Eisenhut F, Elia D, Erazmus B, Ercolessi F, Erhardt F, Ersdal MR, Espagnon B, Eulisse G, Evans D, Evdokimov S, Fabbietti L, Faggin M, Faivre J, Fan F, Fan W, Fantoni A, Fasel M, Fecchio P, Feliciello A, Feofilov G, Fernández Téllez A, Ferrer MB, Ferrero A, Ferrero C, Ferretti A, Feuillard VJG, Filova V, Finogeev D, Fionda FM, Flor F, Flores AN, Foertsch S, Fokin I, Fokin S, Fragiacomo E, Frajna E, Fuchs U, Funicello N, Furget C, Furs A, Fusayasu T, Gaardhøje JJ, Gagliardi M, Gago AM, Galvan CD, Gangadharan DR, Ganoti P, Garabatos C, Garcia JRA, Garcia-Solis E, Garg K, Gargiulo C, Garibli A, Garner K, Gasik P, Gautam A, Gay Ducati MB, Germain M, Ghosh C, Ghosh SK, Giacalone M, Giubellino P, Giubilato P, Glaenzer AMC, Glässel P, Glimos E, Goh DJQ, Gonzalez V, González-Trueba LH, Gorgon M, Gotovac S, Grabski V, Graczykowski LK, Grecka E, Grelli A, Grigoras C, Grigoriev V, Grigoryan S, Grosa F, Grosse-Oetringhaus JF, Grosso R, Grund D, Guardiano GG, Guernane R, Guilbaud M, Gulbrandsen K, Gundem T, Gunji T, Guo W, Gupta A, Gupta R, Guzman SP, Gyulai L, Habib MK, Hadjidakis C, Hamagaki H, Hamdi A, Hamid M, Han Y, Hannigan R, Haque MR, Harris JW, Harton A, Hassan H, Hatzifotiadou D, Hauer P, Havener LB, Heckel ST, Hellbär E, Helstrup H, Hemmer M, Herman T, Herrera Corral G, Herrmann F, Herrmann S, Hetland KF, Heybeck B, Hillemanns H, Hills C, Hippolyte B, Hofman B, Hohlweger B, Honermann J, Hong GH, Horst M, Horzyk A, Hosokawa R, Hou Y, Hristov P, Hughes C, Huhn P, Huhta LM, Hulse CV, Humanic TJ, Hushnud H, Hutson A, Hutter D, Iddon JP, Ilkaev R, Ilyas H, Inaba M, Innocenti GM, Ippolitov M, Isakov A, Isidori T, Islam MS, Ivanov M, Ivanov M, Ivanov V, Izucheev V, Jablonski M, Jacak B, Jacazio N, Jacobs PM, Jadlovska S, Jadlovsky J, Jaelani S, Jaffe L, Jahnke C, Jakubowska MJ, Janik MA, Janson T, Jercic M, Jimenez AAP, Jonas F, Jones PG, Jowett JM, Jung J, Jung M, Junique A, Jusko A, Kabus MJ, Kaewjai J, Kalinak P, Kalteyer AS, Kalweit A, Kaplin V, Karasu Uysal A, Karatovic D, Karavichev O, Karavicheva T, Karczmarczyk P, Karpechev E, Kashyap V, Kebschull U, Keidel R, Keijdener DLD, Keil M, Ketzer B, Khan AM, Khan S, Khanzadeev A, Kharlov Y, Khatun A, Khuntia A, Kileng B, Kim B, Kim C, Kim DJ, Kim EJ, Kim J, Kim JS, Kim J, Kim J, Kim M, Kim S, Kim T, Kimura K, Kirsch S, Kisel I, Kiselev S, Kisiel A, Kitowski JP, Klay JL, Klein J, Klein S, Klein-Bösing C, Kleiner M, Klemenz T, Kluge A, Knospe AG, Kobdaj C, Kollegger T, Kondratyev A, Kondratyuk E, Konig J, Konigstorfer SA, Konopka PJ, Kornakov G, Koryciak SD, Kotliarov A, Kovalenko V, Kowalski M, Kozhuharov V, Králik I, Kravčáková A, Kreis L, Krivda M, Krizek F, Krizkova Gajdosova K, Kroesen M, Krüger M, Krupova DM, Kryshen E, Kučera V, Kuhn C, Kuijer PG, Kumaoka T, Kumar D, Kumar L, Kumar N, Kumar S, Kundu S, Kurashvili P, Kurepin A, Kurepin AB, Kushpil S, Kvapil J, Kweon MJ, Kwon JY, Kwon Y, La Pointe SL, La Rocca P, Lai YS, Lakrathok A, Lamanna M, Langoy R, Larionov P, Laudi E, Lautner L, Lavicka R, Lazareva T, Lea R, Legras G, Lehrbach J, Lemmon RC, León Monzón I, Lesch MM, Lesser ED, Lettrich M, Lévai P, Li X, Li XL, Lien J, Lietava R, Lim B, 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Villalobos Baillie O, Vino G, Vinogradov A, Virgili T, Vislavicius V, Vodopyanov A, Volkel B, Völkl MA, Voloshin K, Voloshin SA, Volpe G, von Haller B, Vorobyev I, Vozniuk N, Vrláková J, Wagner B, Wang C, Wang D, Wegrzynek A, Weiglhofer FT, Wenzel SC, Wessels JP, Weyhmiller SL, Wiechula J, Wikne J, Wilk G, Wilkinson J, Willems GA, Windelband B, Winn M, Wright JR, Wu W, Wu Y, Xu R, Yadav A, Yadav AK, Yalcin S, Yamaguchi Y, Yamakawa K, Yang S, Yano S, Yin Z, Yoo IK, Yoon JH, Yuan S, Yuncu A, Zaccolo V, Zampolli C, Zanoli HJC, Zanone F, Zardoshti N, Zarochentsev A, Závada P, Zaviyalov N, Zhalov M, Zhang B, Zhang L, Zhang S, Zhang X, Zhang Y, Zhang Z, Zhao M, Zherebchevskii V, Zhi Y, Zhigareva N, Zhou D, Zhou Y, Zhu J, Zhu Y, Zinovjev G, Zugravel SC, Zurlo N. Measurement of the Lifetime and Λ Separation Energy of _{Λ}^{3}H. PHYSICAL REVIEW LETTERS 2023; 131:102302. [PMID: 37739380 DOI: 10.1103/physrevlett.131.102302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 01/18/2023] [Accepted: 07/21/2023] [Indexed: 09/24/2023]
Abstract
The most precise measurements to date of the _{Λ}^{3}H lifetime τ and Λ separation energy B_{Λ} are obtained using the data sample of Pb-Pb collisions at sqrt[s_{NN}]=5.02 TeV collected by ALICE at the LHC. The _{Λ}^{3}H is reconstructed via its charged two-body mesonic decay channel (_{Λ}^{3}H→^{3}He+π^{-} and the charge-conjugate process). The measured values τ=[253±11(stat)±6(syst)] ps and B_{Λ}=[102±63(stat)±67(syst)] keV are compatible with predictions from effective field theories and confirm that the _{Λ}^{3}H structure is consistent with a weakly bound system.
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Prasad S, Preghenella R, Prino F, Pruneau CA, Pshenichnov I, Puccio M, Qiu S, Quaglia L, Quishpe RE, Ragoni S, Rakotozafindrabe A, Ramello L, Rami F, Ramirez SAR, Rancien TA, Raniwala R, Raniwala S, Räsänen SS, Rath R, Ravasenga I, Read KF, Redelbach AR, Redlich K, Rehman A, Reichelt P, Reidt F, Reme-Ness HA, Rescakova Z, Reygers K, Riabov A, Riabov V, Ricci R, Richert T, Richter M, Riegler W, Riggi F, Ristea C, Rodríguez Cahuantzi M, Røed K, Rogalev R, Rogochaya E, Rogoschinski TS, Rohr D, Röhrich D, Rojas PF, Rojas Torres S, Rokita PS, Ronchetti F, Rosano A, Rosas ED, Rossi A, Roy A, Roy P, Roy S, Rubini N, Rueda OV, Ruggiano D, Rui R, Rumyantsev B, Russek PG, Russo R, Rustamov A, Ryabinkin E, Ryabov Y, Rybicki A, Rytkonen H, Rzesa W, Saarimaki OAM, Sadek R, Sadovsky S, Saetre J, Šafařík K, Saha SK, Saha S, Sahoo B, Sahoo P, Sahoo R, Sahoo S, Sahu D, Sahu PK, Saini J, Sajdakova K, Sakai S, Salvan MP, Sambyal S, Saramela TB, Sarkar D, Sarkar N, Sarma P, Sarritzu V, Sarti VM, Sas MHP, Schambach J, Scheid HS, Schiaua C, Schicker R, Schmah A, Schmidt C, Schmidt HR, Schmidt MO, Schmidt M, Schmidt NV, Schmier AR, Schotter R, Schukraft J, Schwarz K, Schweda K, Scioli G, Scomparin E, Seger JE, Sekiguchi Y, Sekihata D, Selyuzhenkov I, Senyukov S, Seo JJ, Serebryakov D, Šerkšnytė L, Sevcenco A, Shaba TJ, Shabanov A, Shabetai A, Shahoyan R, Shaikh W, Shangaraev A, Sharma A, Sharma D, Sharma H, Sharma M, Sharma N, Sharma S, Sharma U, Shatat A, Sheibani O, Shigaki K, Shimomura M, Shirinkin S, Shou Q, Sibiriak Y, Siddhanta S, Siemiarczuk T, Silva TF, Silvermyr D, Simantathammakul T, Simeonov R, Simonetti G, Singh B, Singh B, Singh R, Singh R, Singh R, Singh VK, Singhal V, Sinha T, Sitar B, Sitta M, Skaali TB, Skorodumovs G, Slupecki M, Smirnov N, Snellings RJM, Solheim EH, Soncco C, Song J, Songmoolnak A, Soramel F, Sorensen S, Spijkers R, Sputowska I, Staa J, Stachel J, Stan I, Steffanic PJ, Stiefelmaier SF, Stocco D, Storehaug I, Storetvedt MM, Stratmann P, Strazzi S, Stylianidis CP, Suaide AAP, Suire C, Sukhanov M, Suljic M, Sumberia V, Sumowidagdo S, Swain S, Szabo A, Szarka I, Tabassam U, Taghavi SF, Taillepied G, Takahashi J, Tambave GJ, Tang S, Tang Z, Tapia Takaki JD, Tapus N, Tarasovicova LA, Tarzila MG, Tauro A, Telesca A, Terlizzi L, Terrevoli C, Tersimonov G, Thakur S, Thomas D, Tieulent R, Tikhonov A, Timmins AR, Tkacik M, Tkacik T, Toia A, Topilskaya N, Toppi M, Torales-Acosta F, Tork T, Torres Ramos AG, Trifiró A, Triolo AS, Tripathy S, Tripathy T, Trogolo S, Trubnikov V, Trzaska WH, Trzcinski TP, Turrisi R, Tveter TS, Ullaland K, Ulukutlu B, Uras A, Urioni M, Usai GL, Vala M, Valle N, Vallero S, van Doremalen LVR, van Leeuwen M, van Veen CA, van Weelden RJG, Vande Vyvre P, Varga D, Varga Z, Varga-Kofarago M, Vasileiou M, Vasiliev A, Vázquez Doce O, Vechernin V, Vercellin E, Vergara Limón S, Vermunt L, Vértesi R, Verweij M, Vickovic L, Vilakazi Z, Villalobos Baillie O, Vino G, Vinogradov A, Virgili T, Vislavicius V, Vodopyanov A, Volkel B, Völkl MA, Voloshin K, Voloshin SA, Volpe G, von Haller B, Vorobyev I, Vozniuk N, Vrláková J, Wagner B, Wang C, Wang D, Weber M, Wegrzynek A, Weiglhofer FT, Wenzel SC, Wessels JP, Weyhmiller SL, Wiechula J, Wikne J, Wilk G, Wilkinson J, Willems GA, Windelband B, Winn M, Wright JR, Wu W, Wu Y, Xu R, Yadav AK, Yalcin S, Yamaguchi Y, Yamakawa K, Yang S, Yano S, Yin Z, Yoo IK, Yoon JH, Yuan S, Yuncu A, Zaccolo V, Zampolli C, Zanoli HJC, Zanone F, Zardoshti N, Zarochentsev A, Závada P, Zaviyalov N, Zhalov M, Zhang B, Zhang S, Zhang X, Zhang Y, Zhao M, Zherebchevskii V, Zhi Y, Zhigareva N, Zhou D, Zhou Y, Zhu J, Zhu Y, Zinovjev G, Zurlo N. Measurement of the J/ψ Polarization with Respect to the Event Plane in Pb-Pb Collisions at the LHC. PHYSICAL REVIEW LETTERS 2023; 131:042303. [PMID: 37566833 DOI: 10.1103/physrevlett.131.042303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 02/09/2023] [Accepted: 03/28/2023] [Indexed: 08/13/2023]
Abstract
We study the polarization of inclusive J/ψ produced in Pb-Pb collisions at sqrt[s_{NN}]=5.02 TeV at the LHC in the dimuon channel, via the measurement of the angular distribution of its decay products. We perform the study in the rapidity region 2.5
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Acharya S, Adamová D, Adler A, Aglieri Rinella G, Agnello M, Agrawal N, Ahammed Z, Ahmad S, Ahn SU, Ahuja I, Akindinov A, Al-Turany M, Aleksandrov D, Alessandro B, Alfanda HM, Alfaro Molina R, Ali B, Ali Y, Alici A, Alizadehvandchali N, Alkin A, Alme J, Alocco G, Alt T, Altsybeev I, Anaam MN, Andrei C, Andronic A, Anguelov V, Antinori F, Antonioli P, Anuj C, Apadula N, Aphecetche L, Appelshäuser H, Arcelli S, Arnaldi R, Arsene IC, Arslandok M, Augustinus A, Averbeck R, Aziz S, Azmi MD, Badalà A, Baek YW, Bai X, Bailhache R, Bailung Y, Bala R, Balbino A, Baldisseri A, Balis B, Banerjee D, Banoo Z, Barbera R, Barioglio L, Barlou M, Barnaföldi GG, Barnby LS, Barret V, Barreto L, Bartels C, Barth K, Bartsch E, Baruffaldi F, Bastid N, Basu S, Batigne G, Battistini D, Batyunya B, Bauri D, Bazo Alba JL, Bearden IG, Beattie C, Becht P, Behera D, Belikov I, Bell Hechavarria ADC, Bellwied R, Belokurova S, Belyaev V, Bencedi G, Beole S, Bercuci A, Berdnikov Y, Berdnikova A, Bergmann L, Besoiu MG, Betev L, Bhaduri PP, Bhasin A, Bhat IR, Bhat MA, Bhattacharjee B, Bianchi L, Bianchi N, Bielčík J, Bielčíková J, Biernat J, Bilandzic A, Biro G, Biswas S, Blair JT, Blau D, Blidaru MB, Bluhme N, Blume C, Boca G, Bock F, Bodova T, Bogdanov A, Boi S, Bok J, Boldizsár L, Bolozdynya A, Bombara M, Bond PM, Bonomi G, Borel H, Borissov A, Bossi H, Botta E, Bratrud L, Braun-Munzinger P, Bregant M, Broz M, Bruno GE, Buckland MD, Budnikov D, Buesching H, Bufalino S, Bugnon O, Buhler P, Buthelezi Z, Butt JB, Bylinkin A, Bysiak SA, Cai M, Caines H, Caliva A, Calvo Villar E, Camacho JMM, Camacho RS, Camerini P, Canedo FDM, Carabas M, Carnesecchi F, Caron R, Castillo Castellanos J, Catalano F, Ceballos Sanchez C, Chakaberia I, Chakraborty P, Chandra S, Chapeland S, Chartier M, Chattopadhyay S, Chattopadhyay S, Chavez TG, Cheng T, Cheshkov C, Cheynis B, Chibante Barroso V, Chinellato DD, Chizzali ES, Cho S, Chochula P, Christakoglou P, Christensen CH, Christiansen P, Chujo T, Ciacco M, Cicalo C, Cifarelli L, Cindolo F, Ciupek MR, Clai G, Colamaria F, Colburn JS, Colella D, Collu A, Colocci M, Concas M, Conesa Balbastre G, Conesa Del Valle Z, Contin G, Contreras JG, Coquet ML, Cormier TM, Cortese P, Cosentino MR, Costa F, Costanza S, Crochet P, Cruz-Torres R, Cuautle E, Cui P, Cunqueiro L, Dainese A, Danisch MC, Danu A, Das P, Das P, Das S, Dash S, De Caro A, de Cataldo G, De Cilladi L, de Cuveland J, De Falco A, De Gruttola D, De Marco N, De Martin C, De Pasquale S, Deb S, Degenhardt HF, Deja KR, Del Grande R, Dello Stritto L, Deng W, Dhankher P, Di Bari D, Di Mauro A, Diaz RA, Dietel T, Ding Y, Divià R, Dixit DU, Djuvsland Ø, Dmitrieva U, Dobrin A, Dönigus B, Dubey AK, Dubinski JM, Dubla A, Dudi S, Dupieux P, Durkac M, Dzalaiova N, Eder TM, Ehlers RJ, Eikeland VN, Eisenhut F, Elia D, Erazmus B, Ercolessi F, Erhardt F, Erokhin A, Ersdal MR, Espagnon B, Eulisse G, Evans D, Evdokimov S, Fabbietti L, Faggin M, Faivre J, Fan F, Fan W, Fantoni A, Fasel M, Fecchio P, Feliciello A, Feofilov G, Fernández Téllez A, Ferrer MB, Ferrero A, Ferretti A, Feuillard VJG, Figiel J, Filova V, Finogeev D, Fiorenza G, Flor F, Flores AN, Foertsch S, Fokin I, Fokin S, Fragiacomo E, Frajna E, Fuchs U, Funicello N, Furget C, Furs A, Gaardhøje JJ, Gagliardi M, Gago AM, Gal A, Galvan CD, Ganoti P, Garabatos C, Garcia JRA, Garcia-Solis E, Garg K, Gargiulo C, Garibli A, Garner K, Gauger EF, Gautam A, Gay Ducati MB, Germain M, Ghosh SK, Giacalone M, Gianotti P, Giubellino P, Giubilato P, Glaenzer AMC, Glässel P, Glimos E, Goh DJQ, Gonzalez V, González-Trueba LH, Gorbunov S, Gorgon M, Görlich L, Gotovac S, Grabski V, Graczykowski LK, Grecka E, Greiner L, Grelli A, Grigoras C, Grigoriev V, Grigoryan S, Grosa F, Grosse-Oetringhaus JF, Grosso R, Grund D, Guardiano GG, Guernane R, Guilbaud M, Gulbrandsen K, Gunji T, Guo W, Gupta A, Gupta R, Guzman SP, Gyulai L, Habib MK, Hadjidakis C, Hamagaki H, Hamid M, Han Y, Hannigan R, Haque MR, Harlenderova A, Harris JW, Harton A, Hasenbichler JA, Hassan H, Hatzifotiadou D, Hauer P, Havener LB, Heckel ST, Hellbär E, Helstrup H, Herman T, Herrera Corral G, Herrmann F, Hetland KF, Heybeck B, Hillemanns H, Hills C, Hippolyte B, Hofman B, Hohlweger B, Honermann J, Hong GH, Horak D, Horzyk A, Hosokawa R, Hou Y, Hristov P, Hughes C, Huhn P, Huhta LM, Hulse CV, Humanic TJ, Hushnud H, Hutson A, Hutter D, Iddon JP, Ilkaev R, Ilyas H, Inaba M, Innocenti GM, Ippolitov M, Isakov A, Isidori T, Islam MS, Ivanov M, Ivanov V, Izucheev V, Jablonski M, Jacak B, Jacazio N, Jacobs PM, Jadlovska S, Jadlovsky J, Jaffe L, Jahnke C, Janik MA, Janson T, Jercic M, Jevons O, Jimenez AAP, Jonas F, Jones PG, Jowett JM, Jung J, Jung M, Junique A, Jusko A, Kabus MJ, Kaewjai J, Kalinak P, Kalteyer AS, Kalweit A, Kaplin V, Karasu Uysal A, Karatovic D, Karavichev O, Karavicheva T, Karczmarczyk P, Karpechev E, Kashyap V, Kazantsev A, Kebschull U, Keidel R, Keijdener DLD, Keil M, Ketzer B, Khan AM, Khan S, Khanzadeev A, Kharlov Y, Khatun A, Khuntia A, Kileng B, Kim B, Kim C, Kim DJ, Kim EJ, Kim J, Kim JS, Kim J, Kim J, Kim M, Kim S, Kim T, Kirsch S, Kisel I, Kiselev S, Kisiel A, Kitowski JP, Klay JL, Klein J, Klein S, Klein-Bösing C, Kleiner M, Klemenz T, Kluge A, Knospe AG, Kobdaj C, Kollegger T, Kondratyev A, Kondratyeva N, Kondratyuk E, Konig J, Konigstorfer SA, Konopka PJ, Kornakov G, Koryciak SD, Kotliarov A, Kovalenko O, Kovalenko V, Kowalski M, Králik I, Kravčáková A, Kreis L, Krivda M, Krizek F, Krizkova Gajdosova K, Kroesen M, Krüger M, Krupova DM, Kryshen E, Krzewicki M, Kučera V, Kuhn C, Kuijer PG, Kumaoka T, Kumar D, Kumar L, Kumar N, Kundu S, Kurashvili P, Kurepin A, Kurepin AB, Kuryakin A, Kushpil S, Kvapil J, Kweon MJ, Kwon JY, Kwon Y, La Pointe SL, La Rocca P, Lai YS, Lakrathok A, Lamanna M, Langoy R, Larionov P, Laudi E, Lautner L, Lavicka R, Lazareva T, Lea R, Lehrbach J, Lemmon RC, León Monzón I, Lesch MM, Lesser ED, Lettrich M, Lévai P, Li X, Li XL, Lien J, Lietava R, Lim B, Lim SH, Lindenstruth V, Lindner A, Lippmann C, Liu A, Liu DH, Liu J, Lofnes IM, Loginov V, Loizides C, Loncar P, Lopez JA, Lopez X, López Torres E, Lu P, Luhder JR, Lunardon M, Luparello G, Ma YG, Maevskaya A, Mager M, Mahmoud T, Maire A, Malaev M, Malik NM, Malik QW, Malik SK, Malinina L, Mal'Kevich D, Mallick D, Mallick N, Mandaglio G, Manko V, Manso F, Manzari V, Mao Y, Margagliotti GV, Margotti A, Marín A, Markert C, Marquard M, Martin NA, Martinengo P, Martinez JL, Martínez MI, Martínez García G, Masciocchi S, Masera M, Masoni A, Massacrier L, Mastroserio A, Mathis AM, Matonoha O, Matuoka PFT, Matyja A, Mayer C, Mazuecos AL, Mazzaschi F, Mazzilli M, Mdhluli JE, Mechler AF, Melikyan Y, Menchaca-Rocha A, Meninno E, Menon AS, Meres M, Mhlanga S, Miake Y, Micheletti L, Migliorin LC, Mihaylov DL, Mikhaylov K, Mishra AN, Miśkowiec D, Modak A, Mohanty AP, Mohanty B, Mohisin Khan M, Molander MA, Moravcova Z, Mordasini C, Moreira De Godoy DA, Morozov I, Morsch A, Mrnjavac T, Muccifora V, Mudnic E, Muhuri S, Mulligan JD, Mulliri A, Munhoz MG, Munzer RH, Murakami H, Murray S, Musa L, Musinsky J, Myrcha JW, Naik B, Nair R, Nandi BK, Nania R, Nappi E, Nassirpour AF, Nath A, Nattrass C, Nayak TK, Neagu A, Negru A, Nellen L, Nesbo SV, Neskovic G, Nesterov D, Nielsen BS, Nielsen EG, Nikolaev S, Nikulin S, Nikulin V, Noferini F, Noh S, Nomokonov P, Norman J, Novitzky N, Nowakowski P, Nyanin A, Nystrand J, Ogino M, Ohlson A, Okorokov VA, Oleniacz J, Oliveira Da Silva AC, Oliver MH, Onnerstad A, Oppedisano C, Ortiz Velasquez A, Oskarsson A, Otwinowski J, Oya M, Oyama K, Pachmayer Y, Padhan S, Pagano D, Paić G, Palasciano A, Panebianco S, Park J, Parkkila JE, Pathak SP, Patra RN, Paul B, Pei H, Peitzmann T, Peng X, Pereira LG, Pereira Da Costa H, Peresunko D, Perez GM, Perrin S, Pestov Y, Petráček V, Petrov V, Petrovici M, Pezzi RP, Piano S, Pikna M, Pillot P, Pinazza O, Pinsky L, Pinto C, Pisano S, Płoskoń M, Planinic M, Pliquett F, Poghosyan MG, Polichtchouk B, Politano S, Poljak N, Pop A, Porteboeuf-Houssais S, Porter J, Pozdniakov V, Prasad SK, Prasad S, Preghenella R, Prino F, Pruneau CA, Pshenichnov I, Puccio M, Qiu S, Quaglia L, Quishpe RE, Ragoni S, Rakotozafindrabe A, Ramello L, Rami F, Ramirez SAR, Rancien TA, Raniwala R, Raniwala S, Räsänen SS, Rath R, Ravasenga I, Read KF, Redelbach AR, Redlich K, Rehman A, Reichelt P, Reidt F, Reme-Ness HA, Rescakova Z, Reygers K, Riabov A, Riabov V, Ricci R, Richert T, Richter M, Riegler W, Riggi F, Ristea C, Rodríguez Cahuantzi M, Røed K, Rogalev R, Rogochaya E, Rogoschinski TS, Rohr D, Röhrich D, Rojas PF, Rojas Torres S, Rokita PS, Ronchetti F, Rosano A, Rosas ED, Rossi A, Roy A, Roy P, Roy S, Rubini N, Rueda OV, Ruggiano D, Rui R, Rumyantsev B, Russek PG, Russo R, Rustamov A, Ryabinkin E, Ryabov Y, Rybicki A, Rytkonen H, Rzesa W, Saarimaki OAM, Sadek R, Sadovsky S, Saetre J, Šafařík K, Saha SK, Saha S, Sahoo B, Sahoo P, Sahoo R, Sahoo S, Sahu D, Sahu PK, Saini J, Sakai S, Salvan MP, Sambyal S, Saramela TB, Sarkar D, Sarkar N, Sarma P, Sarti VM, Sas MHP, Schambach J, Scheid HS, Schiaua C, Schicker R, Schmah A, Schmidt C, Schmidt HR, Schmidt MO, Schmidt M, Schmidt NV, Schmier AR, Schotter R, Schukraft J, Schwarz K, Schweda K, Scioli G, Scomparin E, Seger JE, Sekiguchi Y, Sekihata D, Selyuzhenkov I, Senyukov S, Seo JJ, Serebryakov D, Šerkšnytė L, Sevcenco A, Shaba TJ, Shabanov A, Shabetai A, Shahoyan R, Shaikh W, Shangaraev A, Sharma A, Sharma D, Sharma H, Sharma M, Sharma N, Sharma S, Sharma U, Shatat A, Sheibani O, Shigaki K, Shimomura M, Shirinkin S, Shou Q, Sibiriak Y, Siddhanta S, Siemiarczuk T, Silva TF, Silvermyr D, Simantathammakul T, Simonetti G, Singh B, Singh B, Singh R, Singh R, Singh R, Singh VK, Singhal V, Sinha T, Sitar B, Sitta M, Skaali TB, Skorodumovs G, Slupecki M, Smirnov N, Snellings RJM, Solheim EH, Soncco C, Song J, Songmoolnak A, Soramel F, Sorensen S, Spijkers R, Sputowska I, Staa J, Stachel J, Stan I, Steffanic PJ, Stiefelmaier SF, Stocco D, Storehaug I, Storetvedt MM, Stratmann P, Strazzi S, Stylianidis CP, Suaide AAP, Suire C, Sukhanov M, Suljic M, Sumberia V, Sumowidagdo S, Swain S, Szabo A, Szarka I, Tabassam U, Taghavi SF, Taillepied G, Takahashi J, Tambave GJ, Tang S, Tang Z, Tapia Takaki JD, Tapus N, Tarasovicova LA, Tarzila MG, Tauro A, Tejeda Muñoz G, Telesca A, Terlizzi L, Terrevoli C, Tersimonov G, Thakur S, Thomas D, Tieulent R, Tikhonov A, Timmins AR, Tkacik M, Tkacik T, Toia A, Topilskaya N, Toppi M, Torales-Acosta F, Tork T, Torres Ramos AG, Trifiró A, Triolo AS, Tripathy S, Tripathy T, Trogolo S, Trubnikov V, Trzaska WH, Trzcinski TP, Tumkin A, Turrisi R, Tveter TS, Ullaland K, Ulukutlu B, Uras A, Urioni M, Usai GL, Vala M, Valle N, Vallero S, van Doremalen LVR, van Leeuwen M, van Veen CA, van Weelden RJG, Vande Vyvre P, Varga D, Varga Z, Varga-Kofarago M, Vasileiou M, Vasiliev A, Vázquez Doce O, Vechernin V, Vercellin E, Vergara Limón S, Vermunt L, Vértesi R, Verweij M, Vickovic L, Vilakazi Z, Villalobos Baillie O, Vino G, Vinogradov A, Virgili T, Vislavicius V, Vodopyanov A, Volkel B, Völkl MA, Voloshin K, Voloshin SA, Volpe G, von Haller B, Vorobyev I, Vozniuk N, Vrláková J, Wagner B, Wang C, Wang D, Weber M, Wegrzynek A, Weiglhofer FT, Wenzel SC, Wessels JP, Weyhmiller SL, Wiechula J, Wikne J, Wilk G, Wilkinson J, Willems GA, Windelband B, Winn M, Wright JR, Wu W, Wu Y, Xu R, Yadav AK, Yalcin S, Yamaguchi Y, Yamakawa K, Yang S, Yano S, Yin Z, Yoo IK, Yoon JH, Yuan S, Yuncu A, Zaccolo V, Zampolli C, Zanoli HJC, Zanone F, Zardoshti N, Zarochentsev A, Závada P, Zaviyalov N, Zhalov M, Zhang B, Zhang S, Zhang X, Zhang Y, Zhao M, Zherebchevskii V, Zhi Y, Zhigareva N, Zhou D, Zhou Y, Zhu J, Zhu Y, Zinovjev G, Zurlo N. First Measurement of Antideuteron Number Fluctuations at Energies Available at the Large Hadron Collider. PHYSICAL REVIEW LETTERS 2023; 131:041901. [PMID: 37566856 DOI: 10.1103/physrevlett.131.041901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 07/01/2022] [Accepted: 09/15/2022] [Indexed: 08/13/2023]
Abstract
The first measurement of event-by-event antideuteron number fluctuations in high energy heavy-ion collisions is presented. The measurements are carried out at midrapidity (|η|<0.8) as a function of collision centrality in Pb-Pb collisions at sqrt[s_{NN}]=5.02 TeV using the ALICE detector. A significant negative correlation between the produced antiprotons and antideuterons is observed in all collision centralities. The results are compared with a state-of-the-art coalescence calculation. While it describes the ratio of higher order cumulants of the antideuteron multiplicity distribution, it fails to describe quantitatively the magnitude of the correlation between antiproton and antideuteron production. On the other hand, thermal-statistical model calculations describe all the measured observables within uncertainties only for correlation volumes that are different with respect to those describing proton yields and a similar measurement of net-proton number fluctuations.
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Acharya S, Adamová D, Adler A, Aglieri Rinella G, Agnello M, Agrawal N, Ahammed Z, Ahmad S, Ahn SU, Ahuja I, Akindinov A, Al-Turany M, Aleksandrov D, Alessandro B, Alfanda HM, Alfaro Molina R, Ali B, Alici A, Alizadehvandchali N, Alkin A, Alme J, Alocco G, Alt T, Altsybeev I, Anaam MN, Andrei C, Andronic A, Anguelov V, Antinori F, Antonioli P, Apadula N, Aphecetche L, Appelshäuser H, Arata C, Arcelli S, Aresti M, Arnaldi R, Arneiro JGMCA, Arsene IC, Arslandok M, Augustinus A, Averbeck R, Azmi MD, Badalà A, Bae J, Baek YW, Bai X, Bailhache R, Bailung Y, Balbino A, Baldisseri A, Balis B, Banerjee D, Banoo Z, Barbera R, Barile F, Barioglio L, Barlou M, Barnaföldi GG, Barnby LS, Barret V, Barreto L, Bartels C, Barth K, Bartsch E, Bastid N, Basu S, Batigne G, Battistini D, Batyunya B, Bauri D, Bazo Alba JL, Bearden IG, Beattie C, Becht P, Behera D, Belikov I, Bell Hechavarria ADC, Bellini F, Bellwied R, Belokurova S, Belyaev V, Bencedi G, Beole S, Bercuci A, Berdnikov Y, Berdnikova A, Bergmann L, Besoiu MG, Betev L, Bhaduri PP, Bhasin A, Bhat MA, Bhattacharjee B, Bianchi L, Bianchi N, Bielčík J, Bielčíková J, Biernat J, Bigot AP, Bilandzic A, Biro G, Biswas S, Bize N, Blair JT, Blau D, Blidaru MB, Bluhme N, Blume C, Boca G, Bock F, Bodova T, Bogdanov A, Boi S, Bok J, Boldizsár L, Bolozdynya A, Bombara M, Bond PM, Bonomi G, Borel H, Borissov A, Borquez Carcamo AG, Bossi H, Botta E, Bouziani YEM, Bratrud L, Braun-Munzinger P, Bregant M, Broz M, Bruno GE, Buckland MD, Budnikov D, Buesching H, Bufalino S, Bugnon O, Buhler P, Buthelezi Z, Bysiak SA, Cai M, Caines H, Caliva A, Calvo Villar E, Camacho JMM, Camerini P, Canedo FDM, Carabas M, Carballo AA, Carnesecchi F, Caron R, Carvalho LAD, Castillo Castellanos J, Catalano F, Ceballos Sanchez C, Chakaberia I, Chakraborty P, Chandra S, Chapeland S, Chartier M, Chattopadhyay S, Chattopadhyay S, Chavez TG, Cheng T, Cheshkov C, Cheynis B, Chibante Barroso V, Chinellato DD, Chizzali ES, Cho J, Cho S, Chochula P, Christakoglou P, Christensen CH, Christiansen P, Chujo T, Ciacco M, Cicalo C, Cindolo F, Ciupek MR, Clai G, Colamaria F, Colburn JS, Colella D, Colocci M, Concas M, Conesa Balbastre G, Conesa Del Valle Z, Contin G, Contreras JG, Coquet ML, Cormier TM, Cortese P, Cosentino MR, Costa F, Costanza S, Cot C, Crkovská J, Crochet P, Cruz-Torres R, Cuautle E, Cui P, Dainese A, Danisch MC, Danu A, Das P, Das P, Das S, Dash AR, Dash S, David RMH, De Caro A, de Cataldo G, de Cuveland J, De Falco A, De Gruttola D, De Marco N, De Martin C, De Pasquale S, Deb S, Debski RJ, Deja KR, Del Grande R, Dello Stritto L, Deng W, Dhankher P, Di Bari D, Di Mauro A, Diaz RA, Dietel T, Ding Y, Divià R, Dixit DU, Djuvsland Ø, Dmitrieva U, Dobrin A, Dönigus B, Dubinski JM, Dubla A, Dudi S, Dupieux P, Durkac M, Dzalaiova N, Eder TM, Ehlers RJ, Eikeland VN, Eisenhut F, Elia D, Erazmus B, Ercolessi F, Erhardt F, Ersdal MR, Espagnon B, Eulisse G, Evans D, Evdokimov S, Fabbietti L, Faggin M, Faivre J, Fan F, Fan W, Fantoni A, Fasel M, Fecchio P, Feliciello A, Feofilov G, Fernández Téllez A, Ferrandi L, Ferrer MB, Ferrero A, Ferrero C, Ferretti A, Feuillard VJG, Filova V, Finogeev D, Fionda FM, Flor F, Flores AN, Foertsch S, Fokin I, Fokin S, Fragiacomo E, Frajna E, Fuchs U, Funicello N, Furget C, Furs A, Fusayasu T, Gaardhøje JJ, Gagliardi M, Gago AM, Galvan CD, Gangadharan DR, Ganoti P, Garabatos C, Garcia JRA, Garcia-Solis E, Garg K, Gargiulo C, Garner K, Gasik P, Gautam A, Gay Ducati MB, Germain M, Ghimouz A, Ghosh C, Giacalone M, Giubellino P, Giubilato P, Glaenzer AMC, Glässel P, Glimos E, Goh DJQ, Gonzalez V, González-Trueba LH, Gorgon M, Gotovac S, Grabski V, Graczykowski LK, Grecka E, Grelli A, Grigoras C, Grigoriev V, Grigoryan S, Grosa F, Grosse-Oetringhaus JF, Grosso R, Grund D, Guardiano GG, Guernane R, Guilbaud M, Gulbrandsen K, Gundem T, Gunji T, Guo W, Gupta A, Gupta R, Guzman SP, Gyulai L, Habib MK, Hadjidakis C, Haider FU, Hamagaki H, Hamdi A, Hamid M, Han Y, Hannigan R, Haque MR, Harris JW, Harton A, Hassan H, Hatzifotiadou D, Hauer P, Havener LB, Heckel ST, Hellbär E, Helstrup H, Hemmer M, Herman T, Herrera Corral G, Herrmann F, Herrmann S, Hetland KF, Heybeck B, Hillemanns H, Hills C, Hippolyte B, Hoffmann FW, Hofman B, Hohlweger B, Hong GH, Horst M, Horzyk A, Hosokawa R, Hou Y, Hristov P, Hughes C, Huhn P, Huhta LM, Hulse CV, Humanic TJ, Hutson A, Hutter D, Iddon JP, Ilkaev R, Ilyas H, Inaba M, Innocenti GM, Ippolitov M, Isakov A, Isidori T, Islam MS, Ivanov M, Ivanov M, Ivanov V, Jablonski M, Jacak B, Jacazio N, Jacobs PM, Jadlovska S, Jadlovsky J, Jaelani S, Jaffe L, Jahnke C, Jakubowska MJ, Janik MA, Janson T, Jercic M, Jia S, Jimenez AAP, Jonas F, Jowett JM, Jung J, Jung M, Junique A, Jusko A, Kabus MJ, Kaewjai J, Kalinak P, Kalteyer AS, Kalweit A, Kaplin V, Karasu Uysal A, Karatovic D, Karavichev O, Karavicheva T, Karczmarczyk P, Karpechev E, Kebschull U, Keidel R, Keijdener DLD, Keil M, Ketzer B, Khan AM, Khan S, Khanzadeev A, Kharlov Y, Khatun A, Khuntia A, Kidson MB, Kileng B, Kim B, Kim C, Kim DJ, Kim EJ, Kim J, Kim JS, Kim J, Kim M, Kim S, Kim T, Kimura K, Kirsch S, Kisel I, Kiselev S, Kisiel A, Kitowski JP, Klay JL, Klein J, Klein S, Klein-Bösing C, Kleiner M, Klemenz T, Kluge A, Knospe AG, Kobdaj C, Kollegger T, Kondratyev A, Kondratyeva N, Kondratyuk E, Konig J, Konigstorfer SA, Konopka PJ, Kornakov G, Koryciak SD, Kotliarov A, Kovalenko V, Kowalski M, Kozhuharov V, Králik I, Kravčáková A, Kreis L, Krivda M, Krizek F, Krizkova Gajdosova K, Kroesen M, Krüger M, Krupova DM, Kryshen E, Kučera V, Kuhn C, Kuijer PG, Kumaoka T, Kumar D, Kumar L, Kumar N, Kumar S, Kundu S, Kurashvili P, Kurepin A, Kurepin AB, Kuryakin A, Kushpil S, Kvapil J, Kweon MJ, Kwon JY, Kwon Y, La Pointe SL, La Rocca P, Lai YS, Lakrathok A, Lamanna M, Langoy R, Larionov P, Laudi E, Lautner L, Lavicka R, Lazareva T, Lea R, Lee H, Legras G, Lehrbach J, Lemmon RC, León Monzón I, Lesch MM, Lesser ED, Lettrich M, Lévai P, Li X, Li XL, Lien J, Lietava R, Likmeta I, Lim B, Lim SH, Lindenstruth V, Lindner A, Lippmann C, Liu A, Liu DH, Liu J, Lofnes IM, Loizides C, Lokos S, Lomker J, Loncar P, Lopez JA, Lopez X, López Torres E, Lu P, Luhder JR, Lunardon M, Luparello G, Ma YG, Maevskaya A, Mager M, Mahmoud T, Maire A, Makariev MV, Malaev M, Malfattore G, Malik NM, Malik QW, Malik SK, Malinina L, Mal'Kevich D, Mallick D, Mallick N, Mandaglio G, Manko V, Manso F, Manzari V, Mao Y, Margagliotti GV, Margotti A, Marín A, Markert C, Martinengo P, Martinez JL, Martínez MI, Martínez García G, Masciocchi S, Masera M, Masoni A, Massacrier L, Mastroserio A, Matonoha O, Matuoka PFT, Matyja A, Mayer C, Mazuecos AL, Mazzaschi F, Mazzilli M, Mdhluli JE, Mechler AF, Melikyan Y, Menchaca-Rocha A, Meninno E, Menon AS, Meres M, Mhlanga S, Miake Y, Micheletti L, Migliorin LC, Mihaylov DL, Mikhaylov K, Mishra AN, Miśkowiec D, Modak A, Mohanty AP, Mohanty B, Mohisin Khan M, Molander MA, Moravcova Z, Mordasini C, Moreira De Godoy DA, Morozov I, Morsch A, Mrnjavac T, Muccifora V, Muhuri S, Mulligan JD, Mulliri A, Munhoz MG, Munzer RH, Murakami H, Murray S, Musa L, Musinsky J, Myrcha JW, Naik B, Nambrath AI, Nandi BK, Nania R, Nappi E, Nassirpour AF, Nath A, Nattrass C, Naydenov MN, Neagu A, Negru A, Nellen L, Nesbo SV, Neskovic G, Nesterov D, Nielsen BS, Nielsen EG, Nikolaev S, Nikulin S, Nikulin V, Noferini F, Noh S, Nomokonov P, Norman J, Novitzky N, Nowakowski P, Nyanin A, Nystrand J, Ogino M, Ohlson A, Okorokov VA, Oleniacz J, Oliveira Da Silva AC, Oliver MH, Onnerstad A, Oppedisano C, Ortiz Velasquez A, Otwinowski J, Oya M, Oyama K, Pachmayer Y, Padhan S, Pagano D, Paić G, Palasciano A, Panebianco S, Park H, Park H, Park J, Parkkila JE, Patra RN, Paul B, Pei H, Peitzmann T, Peng X, Pennisi M, Pereira LG, Peresunko D, Perez GM, Perrin S, Pestov Y, Petráček V, Petrov V, Petrovici M, Pezzi RP, Piano S, Pikna M, Pillot P, Pinazza O, Pinsky L, Pinto C, Pisano S, Płoskoń M, Planinic M, Pliquett F, Poghosyan MG, Polichtchouk B, Politano S, Poljak N, Pop A, Porteboeuf-Houssais S, Pozdniakov V, Pradhan KK, Prasad SK, Prasad S, Preghenella R, Prino F, Pruneau CA, Pshenichnov I, Puccio M, Pucillo S, Pugelova Z, Qiu S, Quaglia L, Quishpe RE, Ragoni S, Rakotozafindrabe A, Ramello L, Rami F, Ramirez SAR, Rancien TA, Rasa M, Räsänen SS, Rath R, Rauch MP, Ravasenga I, Read KF, Reckziegel C, Redelbach AR, Redlich K, Reetz CA, Rehman A, Reidt F, Reme-Ness HA, Rescakova Z, Reygers K, Riabov A, Riabov V, Ricci R, Richter M, Riedel AA, Riegler W, Ristea C, Rodríguez Cahuantzi M, Røed K, Rogalev R, Rogochaya E, Rogoschinski TS, Rohr D, Röhrich D, Rojas PF, Rojas Torres S, Rokita PS, Romanenko G, Ronchetti F, Rosano A, Rosas ED, Roslon K, Rossi A, Roy A, Roy S, Rubini N, Rueda OV, Ruggiano D, Rui R, Rumyantsev B, Russek PG, Russo R, Rustamov A, Ryabinkin E, Ryabov Y, Rybicki A, Rytkonen H, Rzesa W, Saarimaki OAM, Sadek R, Sadhu S, Sadovsky S, Saetre J, Šafařík K, Saha SK, Saha S, Sahoo B, Sahoo R, Sahoo S, Sahu D, Sahu PK, Saini J, Sajdakova K, Sakai S, Salvan MP, Sambyal S, Sanna I, Saramela TB, Sarkar D, Sarkar N, Sarma P, Sarritzu V, Sarti VM, Sas MHP, Schambach J, Scheid HS, Schiaua C, Schicker R, Schmah A, Schmidt C, Schmidt HR, Schmidt MO, Schmidt M, Schmidt NV, Schmier AR, Schotter R, Schröter A, Schukraft J, Schwarz K, Schweda K, Scioli G, Scomparin E, Seger JE, Sekiguchi Y, Sekihata D, Selyuzhenkov I, Senyukov S, Seo JJ, Serebryakov D, Šerkšnytė L, Sevcenco A, Shaba TJ, Shabetai A, Shahoyan R, Shangaraev A, Sharma A, Sharma B, Sharma D, Sharma H, Sharma M, Sharma S, Sharma S, Sharma U, Shatat A, Sheibani O, Shigaki K, Shimomura M, Shin J, Shirinkin S, Shou Q, Sibiriak Y, Siddhanta S, Siemiarczuk T, Silva TF, Silvermyr D, Simantathammakul T, Simeonov R, Singh B, Singh B, Singh R, Singh R, Singh R, Singh S, Singh VK, Singhal V, Sinha T, Sitar B, Sitta M, Skaali TB, Skorodumovs G, Slupecki M, Smirnov N, Snellings RJM, Solheim EH, Song J, Songmoolnak A, Soramel F, Spijkers R, Sputowska I, Staa J, Stachel J, Stan I, Steffanic PJ, Stiefelmaier SF, Stocco D, Storehaug I, Stratmann P, Strazzi S, Stylianidis CP, Suaide AAP, Suire C, Sukhanov M, Suljic M, Sultanov R, Sumberia V, Sumowidagdo S, Swain S, Szarka I, Szymkowski M, Taghavi SF, Taillepied G, Takahashi J, Tambave GJ, Tang S, Tang Z, Tapia Takaki JD, Tapus N, Tarasovicova LA, Tarzila MG, Tassielli GF, Tauro A, Tejeda Muñoz G, Telesca A, Terlizzi L, Terrevoli C, Tersimonov G, Thakur S, Thomas D, Tikhonov A, Timmins AR, Tkacik M, Tkacik T, Toia A, Tokumoto R, Topilskaya N, Toppi M, Torales-Acosta F, Tork T, Torres Ramos AG, Trifiró A, Triolo AS, Tripathy S, Tripathy T, Trogolo S, Trubnikov V, Trzaska WH, Trzcinski TP, Tumkin A, Turrisi R, Tveter TS, Ullaland K, Ulukutlu B, Uras A, Urioni M, Usai GL, Vala M, Valle N, van Doremalen LVR, van Leeuwen M, van Veen CA, van Weelden RJG, Vande Vyvre P, Varga D, Varga Z, Vasileiou M, Vasiliev A, Vázquez Doce O, Vechernin V, Vercellin E, Vergara Limón S, Vermunt L, Vértesi R, Verweij M, Vickovic L, Vilakazi Z, Villalobos Baillie O, Villani A, Vino G, Vinogradov A, Virgili T, Vislavicius V, Vodopyanov A, Volkel B, Völkl MA, Voloshin K, Voloshin SA, Volpe G, von Haller B, Vorobyev I, Vozniuk N, Vrláková J, Wang C, Wang D, Wang Y, Wegrzynek A, Weiglhofer FT, Wenzel SC, Wessels JP, Weyhmiller SL, Wiechula J, Wikne J, Wilk G, Wilkinson J, Willems GA, Windelband B, Winn M, Wright JR, Wu W, Wu Y, Xu R, Yadav A, Yadav AK, Yalcin S, Yamaguchi Y, Yang S, Yano S, Yin Z, Yoo IK, Yoon JH, Yuan S, Yuncu A, Zaccolo V, Zampolli C, Zanone F, Zardoshti N, Zarochentsev A, Závada P, Zaviyalov N, Zhalov M, Zhang B, Zhang L, Zhang S, Zhang X, Zhang Y, Zhang Z, Zhao M, Zherebchevskii V, Zhi Y, Zhou D, Zhou Y, Zhu J, Zhu Y, Zugravel SC, Zurlo N. Enhanced Deuteron Coalescence Probability in Jets. PHYSICAL REVIEW LETTERS 2023; 131:042301. [PMID: 37566840 DOI: 10.1103/physrevlett.131.042301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 04/07/2023] [Accepted: 06/05/2023] [Indexed: 08/13/2023]
Abstract
The transverse-momentum (p_{T}) spectra and coalescence parameters B_{2} of (anti)deuterons are measured in p-p collisions at sqrt[s]=13 TeV for the first time in and out of jets. In this measurement, the direction of the leading particle with the highest p_{T} in the event (p_{T}^{lead}>5 GeV/c) is used as an approximation for the jet axis. The event is consequently divided into three azimuthal regions, and the jet signal is obtained as the difference between the toward region, that contains jet fragmentation products in addition to the underlying event (UE), and the transverse region, which is dominated by the UE. The coalescence parameter in the jet is found to be approximately a factor of 10 larger than that in the underlying event. This experimental observation is consistent with the coalescence picture and can be attributed to the smaller average phase-space distance between nucleons in the jet cone as compared with the underlying event. The results presented in this Letter are compared to predictions from a simple nucleon coalescence model, where the phase-space distributions of nucleons are generated using pythia8 with the Monash 2013 tuning, and to predictions from a deuteron production model based on ordinary nuclear reactions with parametrized energy-dependent cross sections tuned on data. The latter model is implemented in pythia8.3. Both models reproduce the observed large difference between in-jet and out-of-jet coalescence parameters, although the almost flat trend of the B_{2}^{Jet} is not reproduced by the models, which instead give a decreasing trend.
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Yoon JH, Strand F, Baltzer PAT, Conant EF, Gilbert FJ, Lehman CD, Morris EA, Mullen LA, Nishikawa RM, Sharma N, Vejborg I, Moy L, Mann RM. Standalone AI for Breast Cancer Detection at Screening Digital Mammography and Digital Breast Tomosynthesis: A Systematic Review and Meta-Analysis. Radiology 2023; 307:e222639. [PMID: 37219445 PMCID: PMC10315526 DOI: 10.1148/radiol.222639] [Citation(s) in RCA: 27] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 03/23/2023] [Accepted: 04/03/2023] [Indexed: 05/24/2023]
Abstract
Background There is considerable interest in the potential use of artificial intelligence (AI) systems in mammographic screening. However, it is essential to critically evaluate the performance of AI before it can become a modality used for independent mammographic interpretation. Purpose To evaluate the reported standalone performances of AI for interpretation of digital mammography and digital breast tomosynthesis (DBT). Materials and Methods A systematic search was conducted in PubMed, Google Scholar, Embase (Ovid), and Web of Science databases for studies published from January 2017 to June 2022. Sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) values were reviewed. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 and Comparative (QUADAS-2 and QUADAS-C, respectively). A random effects meta-analysis and meta-regression analysis were performed for overall studies and for different study types (reader studies vs historic cohort studies) and imaging techniques (digital mammography vs DBT). Results In total, 16 studies that include 1 108 328 examinations in 497 091 women were analyzed (six reader studies, seven historic cohort studies on digital mammography, and four studies on DBT). Pooled AUCs were significantly higher for standalone AI than radiologists in the six reader studies on digital mammography (0.87 vs 0.81, P = .002), but not for historic cohort studies (0.89 vs 0.96, P = .152). Four studies on DBT showed significantly higher AUCs in AI compared with radiologists (0.90 vs 0.79, P < .001). Higher sensitivity and lower specificity were seen for standalone AI compared with radiologists. Conclusion Standalone AI for screening digital mammography performed as well as or better than radiologists. Compared with digital mammography, there is an insufficient number of studies to assess the performance of AI systems in the interpretation of DBT screening examinations. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Scaranelo in this issue.
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Rho M, Chun SH, Lee E, Lee HS, Yoon JH, Park VY, Han K, Kwak JY. Diagnosis of thyroid micronodules on ultrasound using a deep convolutional neural network. Sci Rep 2023; 13:7231. [PMID: 37142760 PMCID: PMC10160046 DOI: 10.1038/s41598-023-34459-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Accepted: 04/30/2023] [Indexed: 05/06/2023] Open
Abstract
To assess the performance of deep convolutional neural network (CNN) to discriminate malignant and benign thyroid nodules < 10 mm in size and compare the diagnostic performance of CNN with those of radiologists. Computer-aided diagnosis was implemented with CNN and trained using ultrasound (US) images of 13,560 nodules ≥ 10 mm in size. Between March 2016 and February 2018, US images of nodules < 10 mm were retrospectively collected at the same institution. All nodules were confirmed as malignant or benign from aspirate cytology or surgical histology. Diagnostic performances of CNN and radiologists were assessed and compared for area under curve (AUC), sensitivity, specificity, accuracy, positive predictive value, and negative predictive value. Subgroup analyses were performed based on nodule size with a cut-off value of 5 mm. Categorization performances of CNN and radiologists were also compared. A total of 370 nodules from 362 consecutive patients were assessed. CNN showed higher negative predictive value (35.3% vs. 22.6%, P = 0.048) and AUC (0.66 vs. 0.57, P = 0.04) than radiologists. CNN also showed better categorization performance than radiologists. In the subgroup of nodules ≤ 5 mm, CNN showed higher AUC (0.63 vs. 0.51, P = 0.08) and specificity (68.2% vs. 9.1%, P < 0.001) than radiologists. Convolutional neural network trained with thyroid nodules ≥ 10 mm in size showed overall better diagnostic performance than radiologists in the diagnosis and categorization of thyroid nodules < 10 mm, especially in nodules ≤ 5 mm.
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Ahn JH, Go J, Lee SJ, Kim JY, Park HS, Kim SI, Park BW, Park VY, Yoon JH, Kim MJ, Park S. Changes in Automated Mammographic Breast Density Can Predict Pathological Response After Neoadjuvant Chemotherapy in Breast Cancer. Korean J Radiol 2023; 24:384-394. [PMID: 37133209 PMCID: PMC10157320 DOI: 10.3348/kjr.2022.0629] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Revised: 02/08/2023] [Accepted: 03/10/2023] [Indexed: 05/04/2023] Open
Abstract
OBJECTIVE Mammographic density is an independent risk factor for breast cancer that can change after neoadjuvant chemotherapy (NCT). This study aimed to evaluate percent changes in volumetric breast density (ΔVbd%) before and after NCT measured automatically and determine its value as a predictive marker of pathological response to NCT. MATERIALS AND METHODS A total of 357 patients with breast cancer treated between January 2014 and December 2016 were included. An automated volumetric breast density (Vbd) measurement method was used to calculate Vbd on mammography before and after NCT. Patients were divided into three groups according to ΔVbd%, calculated as follows: Vbd (post-NCT - pre-NCT)/pre-NCT Vbd × 100 (%). The stable, decreased, and increased groups were defined as -20% ≤ ΔVbd% ≤ 20%, ΔVbd% < -20%, and ΔVbd% > 20%, respectively. Pathological complete response (pCR) was considered to be achieved after NCT if there was no evidence of invasive carcinoma in the breast or metastatic tumors in the axillary and regional lymph nodes on surgical pathology. The association between ΔVbd% grouping and pCR was analyzed using univariable and multivariable logistic regression analyses. RESULTS The interval between the pre-NCT and post-NCT mammograms ranged from 79 to 250 days (median, 170 days). In the multivariable analysis, ΔVbd% grouping (odds ratio for pCR of 0.420 [95% confidence interval, 0.195-0.905; P = 0.027] for the decreased group compared with the stable group), N stage at diagnosis, histologic grade, and breast cancer subtype were significantly associated with pCR. This tendency was more evident in the luminal B-like and triple-negative subtypes. CONCLUSION ΔVbd% was associated with pCR in breast cancer after NCT, with the decreased group showing a lower rate of pCR than the stable group. Automated measurement of ΔVbd% may help predict the NCT response and prognosis in breast cancer.
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Chung HJ, Han K, Lee E, Yoon JH, Park VY, Lee M, Cho E, Kwak JY. Radiomics Analysis of Gray-Scale Ultrasonographic Images of Papillary Thyroid Carcinoma > 1 cm: Potential Biomarker for the Prediction of Lymph Node Metastasis. JOURNAL OF THE KOREAN SOCIETY OF RADIOLOGY 2023; 84:185-196. [PMID: 36818698 PMCID: PMC9935950 DOI: 10.3348/jksr.2021.0155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Revised: 03/09/2022] [Accepted: 04/19/2022] [Indexed: 02/10/2023]
Abstract
Purpose This study aimed to investigate radiomics analysis of ultrasonographic images to develop a potential biomarker for predicting lymph node metastasis in papillary thyroid carcinoma (PTC) patients. Materials and Methods This study included 431 PTC patients from August 2013 to May 2014 and classified them into the training and validation sets. A total of 730 radiomics features, including texture matrices of gray-level co-occurrence matrix and gray-level run-length matrix and single-level discrete two-dimensional wavelet transform and other functions, were obtained. The least absolute shrinkage and selection operator method was used for selecting the most predictive features in the training data set. Results Lymph node metastasis was associated with the radiomics score (p < 0.001). It was also associated with other clinical variables such as young age (p = 0.007) and large tumor size (p = 0.007). The area under the receiver operating characteristic curve was 0.687 (95% confidence interval: 0.616-0.759) for the training set and 0.650 (95% confidence interval: 0.575-0.726) for the validation set. Conclusion This study showed the potential of ultrasonography-based radiomics to predict cervical lymph node metastasis in patients with PTC; thus, ultrasonography-based radiomics can act as a biomarker for PTC.
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Lee SE, Lee E, Kim EK, Yoon JH, Park VY, Youk JH, Kwak JY. Application of Artificial Intelligence Computer-Assisted Diagnosis Originally Developed for Thyroid Nodules to Breast Lesions on Ultrasound. J Digit Imaging 2022; 35:1699-1707. [PMID: 35902445 PMCID: PMC9712894 DOI: 10.1007/s10278-022-00680-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2021] [Revised: 06/27/2022] [Accepted: 07/11/2022] [Indexed: 10/16/2022] Open
Abstract
As thyroid and breast cancer have several US findings in common, we applied an artificial intelligence computer-assisted diagnosis (AI-CAD) software originally developed for thyroid nodules to breast lesions on ultrasound (US) and evaluated its diagnostic performance. From January 2017 to December 2017, 1042 breast lesions (mean size 20.2 ± 11.8 mm) of 1001 patients (mean age 45.9 ± 12.9 years) who underwent US-guided core-needle biopsy were included. An AI-CAD software that was previously trained and validated with thyroid nodules using the convolutional neural network was applied to breast nodules. There were 665 benign breast lesions (63.0%) and 391 breast cancers (37.0%). The area under the receiver operating characteristic curve (AUROC) of AI-CAD to differentiate breast lesions was 0.678 (95% confidence interval: 0.649, 0.707). After fine-tuning AI-CAD with 1084 separate breast lesions, the diagnostic performance of AI-CAD markedly improved (AUC 0.841). This was significantly higher than that of radiologists when the cutoff category was BI-RADS 4a (AUC 0.621, P < 0.001), but lower when the cutoff category was BI-RADS 4b (AUC 0.908, P < 0.001). When applied to breast lesions, the diagnostic performance of an AI-CAD software that had been developed for differentiating malignant and benign thyroid nodules was not bad. However, an organ-specific approach guarantees better diagnostic performance despite the similar US features of thyroid and breast malignancies.
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Lee SE, Kim GR, Yoon JH, Han K, Son WJ, Shin HJ, Moon HJ. Artificial intelligence assistance for women who had spot compression view: reducing recall rates for digital mammography. Acta Radiol 2022; 64:1808-1815. [PMID: 36426409 DOI: 10.1177/02841851221140556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
Background Mammography yields inevitable recall for indeterminate findings that need to be confirmed with additional views. Purpose To explore whether the artificial intelligence (AI) algorithm for mammography can reduce false-positive recall in patients who undergo the spot compression view. Material and Methods From January to December 2017, 236 breasts from 225 women who underwent the spot compression view due to focal asymmetry, mass, or architectural distortion on standard digital mammography were included. Three readers who were blinded to the study purpose, patient information, previous mammograms, following spot compression views, and any clinical or pathologic reports retrospectively reviewed 236 standard mammograms and determined the necessity of patient recall and the probability of malignancy per breast, first without and then with AI assistance. The performances of AI and the readers were evaluated with the recall rate, area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy. Results Among 236 examinations, 8 (3.4%) were cancers and 228 (96.6%) were benign. The recall rates of all three readers significantly decreased with AI assistance ( P < 0.05). The reader-averaged recall rates significantly decreased with AI assistance regardless of breast composition (fatty breasts: 32.7% to 24.1%m P = 0.002; dense breasts: 33.6% to 21.2%, P < 0.001). The reader-averaged AUC increased with AI assistance and was comparable to that of standalone AI (0.835 vs. 0.895; P = 0.234). The reader-averaged specificity (71.2% to 79.8%, P < 0.001) and accuracy (71.3% to 79.7%, P < 0.001) significantly improved with AI assistance. Conclusion AI assistance significantly reduced false-positive recall without compromising cancer detection in women with focal asymmetry, mass, or architectural distortion on standard digital mammography regardless of mammographic breast density.
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Kim D, Yu J, Kim J, Hwang YA, Kim JK, Ku CR, Yoon JH, Kwak JY, Nam KH, Lee EJ. PSAT376 Utility of lncRNAs in thyroid cancer diagnosis. J Endocr Soc 2022. [DOI: 10.1210/jendso/bvac150.1745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
Abstract
Objectives
Improved molecular testing for common somatic mutations and identification of mRNA and microRNA expression classifiers have emerged as the most promising approaches for diagnosis of thyroid nodules. However, it is necessary to effectively increase diagnostic accuracy further. Currently, lncRNA research has moved to the forefront of human cancer research, as recent findings have revealed a crucial role of lncRNAs in gene modulation. We evaluated the diagnostic value of the selected lncRNAs from The Atlas of Noncoding RNAs in Cancer (TANRIC) thyroid cancer dataset.
Methods
Using TANRIC thyroid cancer dataset, we compared 12,727 lncRNAs from the thyroid cancer tissues of 59 thyroid cancer patients with paired normal thyroid tissues. lncRNAs with significantly increased or decreased expression in thyroid cancer tissues were selected as candidates for thyroid cancer diagnosis. The expression levels of candidate lncRNAs were confirmed in patients with thyroid nodules who underwent surgery at the Severance Hospital. Subsequently, the candidate lncRNAs were applied to actual fine needle aspiration to verify their diagnostic value.
Results
LRRC52-AS1, LINC02471, LINC02082, UNC5B-AS1, LINC02408, MPPED2-AS1, LNCNEF, LOC642484, ATP6V0E2-AS1, and LOC100129129 were selected as candidates for thyroid cancer diagnosis. The expression levels of LRRC52-AS1, LINC02082, UNC5B-AS1, MPPED2-AS1, LNCNEF, and LOC100129129 were significantly increased or decreased in malignant nodules compared to their expression levels in benign nodules or paired normal thyroid tissues in our surgical tissue samples. The combination of LRRC52-AS1, LINC02082, and UNC5B-AS1 showed favorable results, with 89% sensitivity and 100% specificity, for thyroid cancer diagnosis using fine needle aspiration.
Conclusions
lncRNA expression analysis could be a promising approach for advancing molecular diagnosis of thyroid cancer. Further studies are needed to discover lncRNAs of additional diagnostic value.
Presentation: Saturday, June 11, 2022 1:00 p.m. - 3:00 p.m.
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Kim D, Yu J, Kim J, Hwang YA, Kim JK, Ku CR, Yoon JH, Kwak JY, Nam KH, Lee EJ. Use of long non-coding RNAs for the molecular diagnosis of papillary thyroid cancer. Front Oncol 2022; 12:924409. [PMID: 36132147 PMCID: PMC9483125 DOI: 10.3389/fonc.2022.924409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 08/19/2022] [Indexed: 12/03/2022] Open
Abstract
Objective Improved molecular testing for common somatic mutations and the identification of mRNA and microRNA expression classifiers are promising approaches for the diagnosis of thyroid nodules. However, there is a need to improve the diagnostic accuracy of such tests for identifying thyroid cancer. Recent findings have revealed a crucial role of long non-coding RNAs (lncRNAs) in gene modulation. Thus, we aimed to evaluate the diagnostic value of selected lncRNAs from The Atlas of Noncoding RNAs in Cancer (TANRIC) thyroid cancer dataset. Methods LncRNAs in TANRIC thyroid cancer dataset that have significantly increased or decreased expression in papillary thyroid cancer (PTC) tissues were selected as candidates for PTC diagnosis. Surgical specimens from patients who underwent thyroidectomy were used to determine the separation capability of candidate lncRNAs between malignant and benign nodules. Fine needle aspiration samples were obtained and screened for candidate lncRNAs to verify their diagnostic value. Results LRRC52-AS1, LINC02471, LINC02082, UNC5B-AS1, LINC02408, MPPED2-AS1, LNCNEF, LOC642484, ATP6V0E2-AS1, and LOC100129129 were selected as the candidate lncRNAs. LRRC52-AS1, LINC02082, UNC5B-AS1, MPPED2-AS1, LNCNEF, and LOC100129129 expression levels were significantly increased or decreased in malignant nodules compared to those in benign nodules and paired normal thyroid tissues. The combination of LRRC52-AS1, LINC02082, and UNC5B-AS1 showed favorable results for the diagnosis of PTC from fine needle aspirates, with 88.9% sensitivity and 100.0% specificity. Conclusions LncRNA expression analysis is a promising approach for advancing the molecular diagnosis of PTC. Further studies are needed to identify lncRNAs of additional diagnostic value.
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Acharya S, Adamová D, Adler A, Aglieri Rinella G, Agnello M, Agrawal N, Ahammed Z, Ahmad S, Ahn SU, Ahuja I, Akbar Z, Akindinov A, Al-Turany M, Alam SN, Aleksandrov D, Alessandro B, Alfanda HM, Alfaro Molina R, Ali B, Ali Y, Alici A, Alizadehvandchali N, Alkin A, Alme J, Alt T, Altenkamper L, Altsybeev I, Anaam MN, Andrei C, Andreou D, Andronic A, Angeletti M, Anguelov V, Antinori F, Antonioli P, Anuj C, Apadula N, Aphecetche L, Appelshäuser H, Arcelli S, Arnaldi R, Arsene IC, Arslandok M, Augustinus A, Averbeck R, Aziz S, Azmi MD, Badalà A, Baek YW, Bai X, Bailhache R, Bailung Y, Bala R, Balbino A, Baldisseri A, Balis B, Ball M, Banerjee D, Barbera R, Barioglio L, Barlou M, Barnaföldi GG, Barnby LS, Barret V, Bartels C, Barth K, Bartsch E, Baruffaldi F, Bastid N, Basu S, Batigne G, Batyunya B, Bauri D, Bazo Alba JL, Bearden IG, Beattie C, Belikov I, Bell Hechavarria ADC, Bellini F, Bellwied R, Belokurova S, Belyaev V, Bencedi G, Beole S, Bercuci A, Berdnikov Y, Berdnikova A, Bergmann L, Besoiu MG, Betev L, Bhaduri PP, Bhasin A, Bhat IR, Bhat MA, Bhattacharjee B, Bhattacharya P, Bianchi L, Bianchi N, Bielčík J, Bielčíková J, Biernat J, Bilandzic A, Biro G, Biswas S, Blair JT, Blau D, Blidaru MB, Blume C, Boca G, Bock F, Bogdanov A, Boi S, Bok J, Boldizsár L, Bolozdynya A, Bombara M, Bond PM, Bonomi G, Borel H, Borissov A, Bossi H, Botta E, Bratrud L, Braun-Munzinger P, Bregant M, Broz M, Bruno GE, Buckland MD, Budnikov D, Buesching H, Bufalino S, Bugnon O, Buhler P, Buthelezi Z, Butt JB, Bysiak SA, Cai M, Caines H, Caliva A, Calvo Villar E, Camacho JMM, Camacho RS, Camerini P, Canedo FDM, Carnesecchi F, Caron R, Castillo Castellanos J, Casula EAR, Catalano F, Ceballos Sanchez C, Chakraborty P, Chandra S, Chapeland S, Chartier M, Chattopadhyay S, Chattopadhyay S, Chauvin A, Chavez TG, Cheng T, Cheshkov C, Cheynis B, Chibante Barroso V, Chinellato DD, Cho S, Chochula P, Christakoglou P, Christensen CH, Christiansen P, Chujo T, Cicalo C, Cifarelli L, Cindolo F, Ciupek MR, Clai G, Cleymans J, Colamaria F, Colburn JS, Colella D, Collu A, Colocci M, Concas M, Conesa Balbastre G, Conesa Del Valle Z, Contin G, Contreras JG, Coquet ML, Cormier TM, Cortese P, Cosentino MR, Costa F, Costanza S, Crochet P, Cruz-Torres R, Cuautle E, Cui P, Cunqueiro L, Dainese A, Danisch MC, Danu A, Das I, Das P, Das P, Das S, Dash S, De S, De Caro A, de Cataldo G, De Cilladi L, de Cuveland J, De Falco A, De Gruttola D, De Marco N, De Martin C, De Pasquale S, Deb S, Degenhardt HF, Deja KR, Dello Stritto L, Delsanto S, Deng W, Dhankher P, Di Bari D, Di Mauro A, Diaz RA, Dietel T, Ding Y, Divià R, Dixit DU, Djuvsland Ø, Dmitrieva U, Do J, Dobrin A, Dönigus B, Dordic O, Dubey AK, Dubla A, Dudi S, Dukhishyam M, Dupieux P, Dzalaiova N, Eder TM, Ehlers RJ, Eikeland VN, Eisenhut F, Elia D, Erazmus B, Ercolessi F, Erhardt F, Erokhin A, Ersdal MR, Espagnon B, Eulisse G, Evans D, Evdokimov S, Fabbietti L, Faggin M, Faivre J, Fan F, Fantoni A, Fasel M, Fecchio P, Feliciello A, Feofilov G, Fernández Téllez A, Ferrero A, Ferretti A, Feuillard VJG, Figiel J, Filchagin S, Finogeev D, Fionda FM, Fiorenza G, Flor F, Flores AN, Foertsch S, Foka P, Fokin S, Fragiacomo E, Frajna E, Fuchs U, Funicello N, Furget C, Furs A, Gaardhøje JJ, Gagliardi M, Gago AM, Gal A, Galvan CD, Ganoti P, Garabatos C, Garcia JRA, Garcia-Solis E, Garg K, Gargiulo C, Garibli A, Garner K, Gasik P, Gauger EF, Gautam A, Gay Ducati MB, Germain M, Ghosh P, Ghosh SK, Giacalone M, Gianotti P, Giubellino P, Giubilato P, Glaenzer AMC, Glässel P, Goh DJQ, Gonzalez V, González-Trueba LH, Gorbunov S, Gorgon M, Görlich L, Gotovac S, Grabski V, Graczykowski LK, Greiner L, Grelli A, Grigoras C, Grigoriev V, Grigoryan A, Grigoryan S, Groettvik OS, Grosa F, Grosse-Oetringhaus JF, Grosso R, Guardiano GG, Guernane R, Guilbaud M, Gulbrandsen K, Gunji T, Guo W, Gupta A, Gupta R, Guzman SP, Gyulai L, Habib MK, Hadjidakis C, Halimoglu G, Hamagaki H, Hamar G, Hamid M, Hannigan R, Haque MR, Harlenderova A, Harris JW, Harton A, Hasenbichler JA, Hassan H, Hatzifotiadou D, Hauer P, Havener LB, Hayashi S, Heckel ST, Hellbär E, Helstrup H, Herman T, Hernandez EG, Herrera Corral G, Herrmann F, Hetland KF, Hillemanns H, Hills C, Hippolyte B, Hofman B, Hohlweger B, Honermann J, Hong GH, Horak D, Hornung S, Horzyk A, Hosokawa R, Hou Y, Hristov P, Hughes C, Huhn P, Humanic TJ, Hushnud H, Husova LA, Hutson A, Hutter D, Iddon JP, Ilkaev R, Ilyas H, Inaba M, Innocenti GM, Ippolitov M, Isakov A, Islam MS, Ivanov M, Ivanov V, Izucheev V, Jablonski M, Jacak B, Jacazio N, Jacobs PM, Jadlovska S, Jadlovsky J, Jaelani S, Jahnke C, Jakubowska MJ, Jalotra A, Janik MA, Janson T, Jercic M, Jevons O, Jimenez AAP, Jonas F, Jones PG, Jowett JM, Jung J, Jung M, Junique A, Jusko A, Kaewjai J, Kalinak P, Kalweit A, Kaplin V, Kar S, Karasu Uysal A, Karatovic D, Karavichev O, Karavicheva T, Karczmarczyk P, Karpechev E, Kazantsev A, Kebschull U, Keidel R, Keijdener DLD, Keil M, Ketzer B, Khabanova Z, Khan AM, Khan S, Khanzadeev A, Kharlov Y, Khatun A, Khuntia A, Kileng B, Kim B, Kim C, Kim DJ, Kim EJ, Kim J, Kim JS, Kim J, Kim J, Kim J, Kim M, Kim S, Kim T, Kirsch S, Kisel I, Kiselev S, Kisiel A, Kitowski JP, Klay JL, Klein J, Klein S, Klein-Bösing C, Kleiner M, Klemenz T, Kluge A, Knospe AG, Kobdaj C, Köhler MK, Kollegger T, Kondratyev A, Kondratyeva N, Kondratyuk E, Konig J, Konigstorfer SA, Konopka PJ, Kornakov G, Koryciak SD, Koska L, Kotliarov A, Kovalenko O, Kovalenko V, Kowalski M, Králik I, Kravčáková A, Kreis L, Krivda M, Krizek F, Krizkova Gajdosova K, Kroesen M, Krüger M, Kryshen E, Krzewicki M, Kučera V, Kuhn C, Kuijer PG, Kumaoka T, Kumar D, Kumar L, Kumar N, Kundu S, Kurashvili P, Kurepin A, Kurepin AB, Kuryakin A, Kushpil S, Kvapil J, Kweon MJ, Kwon JY, Kwon Y, La Pointe SL, La Rocca P, Lai YS, Lakrathok A, Lamanna M, Langoy R, Lapidus K, Larionov P, Laudi E, Lautner L, Lavicka R, Lazareva T, Lea R, Lehrbach J, Lemmon RC, León Monzón I, Lesser ED, Lettrich M, Lévai P, Li X, Li XL, Lien J, Lietava R, Lim B, Lim SH, Lindenstruth V, Lindner A, Lippmann C, Liu A, Liu DH, Liu J, Lofnes IM, Loginov V, Loizides C, Loncar P, Lopez JA, Lopez X, López Torres E, Luhder JR, Lunardon M, Luparello G, Ma YG, Maevskaya A, Mager M, Mahmoud T, Maire A, Malaev M, Malik NM, Malik QW, Malinina L, Mal'Kevich D, Mallick N, Malzacher P, Mandaglio G, Manko V, Manso F, Manzari V, Mao Y, Mareš J, Margagliotti GV, Margotti A, Marín A, Markert C, Marquard M, Martin NA, Martinengo P, Martinez JL, Martínez MI, Martínez García G, Masciocchi S, Masera M, Masoni A, Massacrier L, Mastroserio A, Mathis AM, Matonoha O, Matuoka PFT, Matyja A, Mayer C, Mazuecos AL, Mazzaschi F, Mazzilli M, Mazzoni MA, Mdhluli JE, Mechler AF, Meddi F, Melikyan Y, Menchaca-Rocha A, Meninno E, Menon AS, Meres M, Mhlanga S, Miake Y, Micheletti L, Migliorin LC, Mihaylov DL, Mikhaylov K, Mishra AN, Miśkowiec D, Modak A, Mohanty AP, Mohanty B, Mohisin Khan M, Molander MA, Moravcova Z, Mordasini C, Moreira De Godoy DA, Moreno LAP, Morozov I, Morsch A, Mrnjavac T, Muccifora V, Mudnic E, Mühlheim D, Muhuri S, Mulligan JD, Mulliri A, Munhoz MG, Munzer RH, Murakami H, Murray S, Musa L, Musinsky J, Myrcha JW, Naik B, Nair R, Nandi BK, Nania R, Nappi E, Nassirpour AF, Nath A, Nattrass C, Neagu A, Nellen L, Nesbo SV, Neskovic G, Nesterov D, Nielsen BS, Nikolaev S, Nikulin S, Nikulin V, Noferini F, Noh S, Nomokonov P, Norman J, Novitzky N, Nowakowski P, Nyanin A, Nystrand J, Ogino M, Ohlson A, Okorokov VA, Oleniacz J, Oliveira Da Silva AC, Oliver MH, Onnerstad A, Oppedisano C, Ortiz Velasquez A, Osako T, Oskarsson A, Otwinowski J, Oya M, Oyama K, Pachmayer Y, Padhan S, Pagano D, Paić G, Palasciano A, Pan J, Panebianco S, Pareek P, Park J, Parkkila JE, Pathak SP, Patra RN, Paul B, Pei H, Peitzmann T, Peng X, Pereira LG, Pereira Da Costa H, Peresunko D, Perez GM, Perrin S, Pestov Y, Petráček V, Petrovici M, Pezzi RP, Piano S, Pikna M, Pillot P, Pinazza O, Pinsky L, Pinto C, Pisano S, Płoskoń M, Planinic M, Pliquett F, Poghosyan MG, Polichtchouk B, Politano S, Poljak N, Pop A, Porteboeuf-Houssais S, Porter J, Pozdniakov V, Prasad SK, Preghenella R, Prino F, Pruneau CA, Pshenichnov I, Puccio M, Qiu S, Quaglia L, Quishpe RE, Ragoni S, Rakotozafindrabe A, Ramello L, Rami F, Ramirez SAR, Ramos AGT, Rancien TA, Raniwala R, Raniwala S, Räsänen SS, Rath R, Ravasenga I, Read KF, Redelbach AR, Redlich K, Rehman A, Reichelt P, Reidt F, Reme-Ness HA, Renfordt R, Rescakova Z, Reygers K, Riabov A, Riabov V, Richert T, Richter M, Riegler W, Riggi F, Ristea C, Rodríguez Cahuantzi M, Røed K, Rogalev R, Rogochaya E, Rogoschinski TS, Rohr D, Röhrich D, Rojas PF, Rokita PS, Ronchetti F, Rosano A, Rosas ED, Rossi A, Rotondi A, Roy A, Roy P, Roy S, Rubini N, Rueda OV, Rui R, Rumyantsev B, Russek PG, Rustamov A, Ryabinkin E, Ryabov Y, Rybicki A, Rytkonen H, Rzesa W, Saarimaki OAM, Sadek R, Sadovsky S, Saetre J, Šafařík K, Saha SK, Saha S, Sahoo B, Sahoo P, Sahoo R, Sahoo S, Sahu D, Sahu PK, Saini J, Sakai S, Sambyal S, Samsonov V, Sarkar D, Sarkar N, Sarma P, Sarti VM, Sas MHP, Schambach J, Scheid HS, Schiaua C, Schicker R, Schmah A, Schmidt C, Schmidt HR, Schmidt MO, Schmidt M, Schmidt NV, Schmier AR, Schotter R, Schukraft J, Schutz Y, Schwarz K, Schweda K, Scioli G, Scomparin E, Seger JE, Sekiguchi Y, Sekihata D, Selyuzhenkov I, Senyukov S, Seo JJ, Serebryakov D, Šerkšnytė L, Sevcenco A, Shaba TJ, Shabanov A, Shabetai A, Shahoyan R, Shaikh W, Shangaraev A, Sharma A, Sharma H, Sharma M, Sharma N, Sharma S, Sharma U, Sheibani O, Shigaki K, Shimomura M, Shirinkin S, Shou Q, Sibiriak Y, Siddhanta S, Siemiarczuk T, Silva TF, Silvermyr D, Simantathammakul T, Simonetti G, Singh B, Singh R, Singh R, Singh R, Singh VK, Singhal V, Sinha T, Sitar B, Sitta M, Skaali TB, Skorodumovs G, Slupecki M, Smirnov N, Snellings RJM, Soncco C, Song J, Songmoolnak A, Soramel F, Sorensen S, Sputowska I, Stachel J, Stan I, Steffanic PJ, Stiefelmaier SF, Stocco D, Storehaug I, Storetvedt MM, Stylianidis CP, Suaide AAP, Sugitate T, Suire C, Sukhanov M, Suljic M, Sultanov R, Šumbera M, Sumberia V, Sumowidagdo S, Swain S, Szabo A, Szarka I, Tabassam U, Taghavi SF, Taillepied G, Takahashi J, Tambave GJ, Tang S, Tang Z, Tarhini M, Tarzila MG, Tauro A, Tejeda Muñoz G, Telesca A, Terlizzi L, Terrevoli C, Tersimonov G, Thakur S, Thomas D, Tieulent R, Tikhonov A, Timmins AR, Tkacik M, Toia A, Topilskaya N, Toppi M, Torales-Acosta F, Tork T, Torres SR, Trifiró A, Tripathy S, Tripathy T, Trogolo S, Trombetta G, Trubnikov V, Trzaska WH, Trzcinski TP, Trzeciak BA, Tumkin A, Turrisi R, Tveter TS, Ullaland K, Uras A, Urioni M, Usai GL, Vala M, Valle N, Vallero S, van der Kolk N, van Doremalen LVR, van Leeuwen M, Vande Vyvre P, Varga D, Varga Z, Varga-Kofarago M, Vargas A, Vasileiou M, Vasiliev A, Vázquez Doce O, Vechernin V, Vercellin E, Vergara Limón S, Vermunt L, Vértesi R, Verweij M, Vickovic L, Vilakazi Z, Villalobos Baillie O, Vino G, Vinogradov A, Virgili T, Vislavicius V, Vodopyanov A, Volkel B, Völkl MA, Voloshin K, Voloshin SA, Volpe G, von Haller B, Vorobyev I, Voscek D, Vozniuk N, Vrláková J, Wagner B, Wang C, Wang D, Weber M, Weelden RJGV, Wegrzynek A, Wenzel SC, Wessels JP, Wiechula J, Wikne J, Wilk G, Wilkinson J, Willems GA, Windelband B, Winn M, Witt WE, Wright JR, Wu W, Wu Y, Xu R, Yadav AK, Yalcin S, Yamaguchi Y, Yamakawa K, Yang S, Yano S, Yin Z, Yokoyama H, Yoo IK, Yoon JH, Yuan S, Yuncu A, Zaccolo V, Zampolli C, Zanoli HJC, Zardoshti N, Zarochentsev A, Závada P, Zaviyalov N, Zhalov M, Zhang B, Zhang S, Zhang X, Zhang Y, Zherebchevskii V, Zhi Y, Zhigareva N, Zhou D, Zhou Y, Zhu J, Zhu Y, Zichichi A, Zinovjev G, Zurlo N. Hypertriton Production in p-Pb Collisions at sqrt[s_{NN}]=5.02 TeV. PHYSICAL REVIEW LETTERS 2022; 128:252003. [PMID: 35802430 DOI: 10.1103/physrevlett.128.252003] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Revised: 01/28/2022] [Accepted: 06/03/2022] [Indexed: 06/15/2023]
Abstract
The study of nuclei and antinuclei production has proven to be a powerful tool to investigate the formation mechanism of loosely bound states in high-energy hadronic collisions. The first measurement of the production of _{Λ}^{3}H in p-Pb collisions at sqrt[s_{NN}]=5.02 TeV is presented in this Letter. Its production yield measured in the rapidity interval -1<y<0 for the 40% highest-multiplicity p-Pb collisions is dN/dy=[6.3±1.8(stat)±1.2(syst)]×10^{-7}. The measurement is compared with the expectations of statistical hadronization and coalescence models, which describe the nucleosynthesis in hadronic collisions. These two models predict very different yields of the hypertriton in charged particle multiplicity environments relevant to small collision systems such as p-Pb, and therefore the measurement of dN/dy is crucial to distinguish between them. The precision of this measurement leads to the exclusion with a significance larger than 6.9σ of some configurations of the statistical hadronization model, thus constraining the theory behind the production of loosely bound states at hadron colliders.
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