Integrative radiopathomics model for predicting progression-free survival in patients with nonmetastatic nasopharyngeal carcinoma

Alvarez-Jimenez C, Sandino AA, Prasanna P, Gupta A, Viswanath SE, Romero E (2020) Identifying Cross-scale associations between Radiomic and Pathomic signatures of Non-small Cell Lung Cancer subtypes: preliminary results. Cancers (Basel) 12. https://doi.org/10.3390/cancers12123663

Bologna M, Corino V, Calareso G, Tenconi C, Alfieri S, Iacovelli NA, Cavallo A, Cavalieri S, Locati L, Bossi P, Romanello DA, Ingargiola R, Rancati T, Pignoli E, Sdao S, Pecorilla M, Facchinetti N, Trama A, Licitra L, Mainardi L, Orlandi E (2020) Baseline MRI-Radiomics can predict overall survival in non-endemic EBV-Related nasopharyngeal carcinoma patients. Cancers (Basel) 12. https://doi.org/10.3390/cancers12102958

Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A (2018) Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 68:394–424. https://doi.org/10.3322/caac.21492

Article  PubMed  Google Scholar 

Chen F-P, Lin L, Qi Z-Y, Zhou G-Q, Guo R, Hu J, Lin A-H, Ma J, Sun Y (2017) Pretreatment nomograms for local and Regional Recurrence after Radical Radiation Therapy for Primary Nasopharyngeal Carcinoma. J Cancer 8:2595–2603. https://doi.org/10.7150/jca.20255

Article  PubMed  PubMed Central  CAS  Google Scholar 

Chu LC, Park S, Kawamoto S, Fouladi DF, Shayesteh S, Zinreich ES, Graves JS, Horton KM, Hruban RH, Yuille AL, Kinzler KW, Vogelstein B, Fishman EK (2019) Utility of CT Radiomics Features in differentiation of pancreatic ductal adenocarcinoma from normal pancreatic tissue. AJR Am J Roentgenol 213:349–357. https://doi.org/10.2214/AJR.18.20901

Article  PubMed  Google Scholar 

Feng L, Liu Z, Li C, Li Z, Lou X, Shao L, Wang Y, Huang Y, Chen H, Pang X, Liu S, He F, Zheng J, Meng X, Xie P, Yang G, Ding Y, Wei M, Yun J, Hung M-C, Zhou W, Wahl DR, Lan P, Tian J, Wan X (2022) Development and validation of a radiopathomics model to predict pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer: a multicentre observational study. Lancet Digit Health 4:e8–e17. https://doi.org/10.1016/S2589-7500(21)00215-6

Article  PubMed  CAS  Google Scholar 

Hatt M, Tixier F, Visvikis D, Le Cheze Rest C (2017) Radiomics in PET/CT: more than meets the Eye? J Nucl Med 58:365–366. https://doi.org/10.2967/jnumed.116.184655

Article  PubMed  Google Scholar 

He S, Wang Y, Chen H, Yang L, Liang S, Lu L, Chen Y (2016) C-Reactive Protein/Albumin ratio (CAR) as a prognostic factor in patients with non-metastatic nasopharyngeal carcinoma. J Cancer 7:2360–2366. https://doi.org/10.7150/jca.16443

Article  PubMed  PubMed Central  Google Scholar 

Kather JN, Pearson AT, Halama N, Jäger D, Krause J, Loosen SH, Marx A, Boor P, Tacke F, Neumann UP, Grabsch HI, Yoshikawa T, Brenner H, Chang-Claude J, Hoffmeister M, Trautwein C, Luedde T (2019) Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer. Nat Med 25:1054–1056. https://doi.org/10.1038/s41591-019-0462-y

Article  PubMed  PubMed Central  CAS  Google Scholar 

Kuo MD, Jamshidi N (2014) Behind the numbers: decoding molecular phenotypes with radiogenomics–guiding principles and technical considerations. Radiology 270:320–325. https://doi.org/10.1148/radiol.13132195

Article  PubMed  Google Scholar 

Lambrechts D, Wauters E, Boeckx B, Aibar S, Nittner D, Burton O, Bassez A, Decaluwé H, Pircher A, van den Eynde K, Weynand B, Verbeken E, de Leyn P, Liston A, Vansteenkiste J, Carmeliet P, Aerts S, Thienpont B (2018) Phenotype molding of stromal cells in the lung tumor microenvironment. Nat Med 24:1277–1289. https://doi.org/10.1038/s41591-018-0096-5

Article  PubMed  CAS  Google Scholar 

Lee S, Choi Y, Seo M-K, Jang J, Shin N-Y, Ahn K-J, Kim B-S (2022) Magnetic resonance imaging-based Radiomics for the prediction of progression-free survival in patients with Nasopharyngeal Carcinoma: a systematic review and Meta-analysis. Cancers (Basel) 14. https://doi.org/10.3390/cancers14030653

Liu K, Xia W, Qiang M, Chen X, Liu J, Guo X, Lv X (2020) Deep learning pathological microscopic features in endemic nasopharyngeal cancer: prognostic value and protentional role for individual induction chemotherapy. Cancer Med 9:1298–1306. https://doi.org/10.1002/cam4.2802

Article  PubMed  CAS  Google Scholar 

Ono T, Azuma K, Kawahara A, Sasada T, Matsuo N, Kakuma T, Kamimura H, Maeda R, Hattori C, On K, Nagata K, Sato F, Chitose S-I, Shin B, Aso T, Akiba J, Umeno H (2018) Prognostic stratification of patients with nasopharyngeal carcinoma based on tumor immune microenvironment. Head Neck 40:2007–2019. https://doi.org/10.1002/hed.25189

Article  PubMed  Google Scholar 

Pan JJ, Ng WT, Zong JF, Chan LLK, O’Sullivan B, Lin SJ, Sze HCK, Chen YB, Choi HCW, Guo QJ, Kan WK, Xiao YP, Wei X, Le QT, Glastonbury CM, Colevas AD, Weber RS, Shah JP, Lee AWM (2016) Proposal for the 8th edition of the AJCC/UICC staging system for nasopharyngeal cancer in the era of intensity-modulated radiotherapy. Cancer 122:546–558. https://doi.org/10.1002/cncr.29795

Article  PubMed  Google Scholar 

Pantanowitz L, Quiroga-Garza GM, Bien L, Heled R, Laifenfeld D, Linhart C, Sandbank J, Albrecht Shach A, Shalev V, Vecsler M, Michelow P, Hazelhurst S, Dhir R (2020) An artificial intelligence algorithm for prostate cancer diagnosis in whole slide images of core needle biopsies: a blinded clinical validation and deployment study. Lancet Digit Health 2:e407–e416. https://doi.org/10.1016/S2589-7500(20)30159-X

Article  PubMed  Google Scholar 

Pfister DG, Spencer S, Adelstein D, Adkins D, Anzai Y, Brizel DM, Bruce JY, Busse PM, Caudell JJ, Cmelak AJ, Colevas AD, Eisele DW, Fenton M, Foote RL, Galloway T, Gillison ML, Haddad RI, Hicks WL, Hitchcock YJ, Jimeno A, Leizman D, Maghami E, Mell LK, Mittal BB, Pinto HA, Ridge JA, Rocco JW, Rodriguez CP, Shah JP, Weber RS, Weinstein G, Witek M, Worden F, Yom SS, Zhen W, Burns JL, Darlow SD (2020) Head and Neck cancers, Version 2.2020, NCCN Clinical Practice guidelines in Oncology. J Natl Compr Canc Netw 18:873–898. https://doi.org/10.6004/jnccn.2020.0031

Article  PubMed  Google Scholar 

Saednia K, Lagree A, Alera MA, Fleshner L, Shiner A, Law E, Law B, Dodington DW, Lu F-I, Tran WT, Sadeghi-Naini A (2022) Quantitative digital histopathology and machine learning to predict pathological complete response to chemotherapy in breast cancer patients using pre-treatment tumor biopsies. Sci Rep 12:9690. https://doi.org/10.1038/s41598-022-13917-4

Article  PubMed  PubMed Central  CAS  Google Scholar 

Shao L, Liu Z, Feng L, Lou X, Li Z, Zhang X-Y, Wan X, Zhou X, Sun K, Zhang D-F, Wu L, Yang G, Sun Y-S, Xu R, Fan X, Tian J (2020) Multiparametric MRI and whole slide image-based pretreatment prediction of pathological response to Neoadjuvant Chemoradiotherapy in rectal Cancer: a Multicenter Radiopathomic Study. Ann Surg Oncol 27:4296–4306. https://doi.org/10.1245/s10434-020-08659-4

Article  PubMed  PubMed Central  Google Scholar 

Skrede O-J, de Raedt S, Kleppe A, Hveem TS, Liestøl K, Maddison J, Askautrud HA, Pradhan M, Nesheim JA, Albregtsen F, Farstad IN, Domingo E, Church DN, Nesbakken A, Shepherd NA, Tomlinson I, Kerr R, Novelli M, Kerr DJ, Danielsen HE (2020) Deep learning for prediction of colorectal cancer outcome: a discovery and validation study. Lancet 395:350–360. https://doi.org/10.1016/S0140-6736(19)32998-8

Article  PubMed  CAS  Google Scholar 

Spadarella G, Calareso G, Garanzini E, Ugga L, Cuocolo A, Cuocolo R (2021) MRI based radiomics in nasopharyngeal cancer: systematic review and perspectives using radiomic quality score (RQS) assessment. Eur J Radiol 140:109744. https://doi.org/10.1016/j.ejrad.2021.109744

Article  PubMed  Google Scholar 

Travis WD, Brambilla E, Riely GJ (2013) New pathologic classification of lung cancer: relevance for clinical practice and clinical trials. J Clin Oncol 31:992–1001. https://doi.org/10.1200/JCO.2012.46.9270

Article  PubMed  CAS  Google Scholar 

Wang Y-Q, Chen Y-P, Zhang Y, Jiang W, Liu N, Yun J-P, Sun Y, He Q-M, Tang X-R, Wen X, Yang X-J, Zhang P-P, Zhang J, Lei Y, Li Y-Q, Ma J (2018) Prognostic significance of tumor-infiltrating lymphocytes in nondisseminated nasopharyngeal carcinoma: a large-scale cohort study. Int J Cancer 142:2558–2566. https://doi.org/10.1002/ijc.31279

Article  PubMed  CAS  Google Scholar 

Wu S, Li H, Dong A, Tian L, Ruan G, Liu L, Shao Y (2021) Differences in Radiomics Signatures between Patients with early and advanced T-Stage Nasopharyngeal Carcinoma Facilitate Prognostication. J Magn Reson Imaging 54:854–865. https://doi.org/10.1002/jmri.27633

Article  PubMed  Google Scholar 

Yang K, Tian J, Zhang B, Li M, Xie W, Zou Y, Tan Q, Liu L, Zhu J, Shou A, Li G (2019) A multidimensional nomogram combining overall stage, dose volume histogram parameters and radiomics to predict progression-free survival in patients with locoregionally advanced nasopharyngeal carcinoma. Oral Oncol 98:85–91. https://doi.org/10.1016/j.oraloncology.2019.09.022

Article  PubMed  CAS  Google Scholar 

You R, Liu Y-P, Lin M, Huang P-Y, Tang L-Q, Zhang Y-N, Pan Y, Liu W-L, Guo W-B, Zou X, Zhao K-M, Kang T, Liu L-Z, Lin A-H, Hong M-H, Mai H-Q, Zeng M-S, Chen M-Y (2019) Relationship of circulating tumor cells and Epstein-Barr virus DNA to progression-free survival and overall survival in metastatic nasopharyngeal carcinoma patients. Int J Cancer 145:2873–2883. https://doi.org/10.1002/ijc.32380

Article  PubMed  CAS  Google Scholar 

Zhang B, Tian J, Di Dong, Gu D, Dong Y, Zhang L, Lian Z, Liu J, Luo X, Pei S, Mo X, Huang W, Ouyang F, Guo B, Liang L, Chen W, Liang C, Zhang S (2017) Radiomics Features of Multiparametric MRI as Novel prognostic factors in Advanced Nasopharyngeal Carcinoma. Clin Cancer Res 23:4259–4269. https://doi.org/10.1158/1078-0432.CCR-16-2910

Article  PubMed  Google Scholar 

Zhang F, Zhong L-Z, Zhao X, Di Dong, Yao J-J, Wang S-Y, Liu Y, Zhu D, Wang Y, Wang G-J, Wang Y-M, Li D, Wei J, Tian J, Shan H (2020) A deep-learning-based prognostic nomogram integrating microscopic digital path

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