Swerdlow SH, Campo E, Pileri SA, Harris NL, Stein H, Siebert R, et al. The 2016 revision of the World Health Organization classification of lymphoid neoplasms. Blood. 2016;127:2375–90. https://doi.org/10.1182/blood-2016-01-643569.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Kwak JY. Treatment of diffuse large B cell lymphoma. Korean J Intern Med. 2012;27:369–77. https://doi.org/10.3904/kjim.2012.27.4.369.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Zhou Z, Sehn LH, Rademaker AW, Gordon LI, Lacasce AS, Crosby-Thompson A, et al. An enhanced International Prognostic Index (NCCN-IPI) for patients with diffuse large B-cell lymphoma treated in the rituximab era. Blood. 2014;123:837–42. https://doi.org/10.1182/blood-2013-09-524108.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Shipp MAHD. A predictive model for aggressive non-Hodgkin’s lymphomas. The international non-Hodgkin’s lymphoma prognostic factors project. N Engl J Med. 1993;329(14):987–94.

Article  Google Scholar 

Seo S, Hong JY, Yoon S, Yoo C, Park JH, Lee JB, et al. Prognostic significance of serum beta-2 microglobulin in patients with diffuse large B-cell lymphoma in the rituximab era. Oncotarget. 2016;7:76934–43.

Article  PubMed  PubMed Central  Google Scholar 

Kanemasa Y, Shimoyama T, Sasaki Y, Tamura M, Sawada T, Omuro Y, et al. Beta-2 microglobulin as a significant prognostic factor and a new risk model for patients with diffuse large B-cell lymphoma. Hematol Oncol. 2017;35:440–6. https://doi.org/10.1002/hon.2312.

Article  CAS  PubMed  Google Scholar 

Vaidya R, Witzig TE. Prognostic factors for diffuse large B-cell lymphoma in the R(X)CHOP era. Ann Oncol. 2014;25:2124–33. https://doi.org/10.1093/annonc/mdu109.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Vercellino L, Cottereau AS, Casasnovas O, Tilly H, Feugier P, Chartier L, et al. High total metabolic tumor volume at baseline predicts survival independent of response to therapy. Blood. 2020;135:1396–405.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Frood R, Burton C, Tsoumpas C, Frangi AF, Gleeson F, Patel C, et al. Baseline PET/CT imaging parameters for prediction of treatment outcome in Hodgkin and diffuse large B cell lymphoma: a systematic review. Eur J Nucl Med Mol Imaging. 2021;48:3198–220. https://doi.org/10.1007/s00259-021-05233-2.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Schmitz C, Huttmann A, Muller SP, Hanoun M, Boellaard R, Brinkmann M, et al. Dynamic risk assessment based on positron emission tomography scanning in diffuse large B-cell lymphoma: Post-hoc analysis from the PETAL trial. Eur J Cancer. 2020;124:25–36. https://doi.org/10.1016/j.ejca.2019.09.027.

Article  CAS  PubMed  Google Scholar 

Cottereau AS, Lanic H, Mareschal S, Meignan M, Vera P, Tilly H, et al. Molecular profile and FDG-PET metabolic volume at staging in DLBCL-response. Clin Cancer Res. 2016;22:3414–5. https://doi.org/10.1158/1078-0432.CCR-16-0783.

Article  PubMed  Google Scholar 

Mikhaeel NG, Smith D, Dunn JT, Phillips M, Moller H, Fields PA, et al. Combination of baseline metabolic tumour volume and early response on PET/CT improves progression-free survival prediction in DLBCL. Eur J Nucl Med Mol Imaging. 2016;43:1209–19. https://doi.org/10.1007/s00259-016-3315-7.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Cottereau AS, Nioche C, Dirand AS, Clerc J, Morschhauser F, Casasnovas O, et al. (18)F-FDG PET dissemination features in diffuse large B-Cell lymphoma are predictive of outcome. J Nucl Med. 2020;61:40–5. https://doi.org/10.2967/jnumed.119.229450.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Suguro M, Yoshida N, Umino A, Kato H, Tagawa H, Nakagawa M, et al. Clonal heterogeneity of lymphoid malignancies correlates with poor prognosis. Cancer Sci. 2014;105:897–904. https://doi.org/10.1111/cas.12442.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Khan S, Naim S, Bilwani R, Salem A, Gorlin D, Muhammad A, et al. Radiogenomics and its role in lymphoma. Curr Hematol Malig Rep. 2020;15:211–24. https://doi.org/10.1007/s11899-020-00577-2.

Article  PubMed  Google Scholar 

Lue KH, Wu YF, Lin HH, Hsieh TC, Liu SH, Chan SC, et al. Prognostic value of baseline radiomic features of (18)F-FDG PET in patients with diffuse large B-cell lymphoma. Diagnostics (Basel). 2020. https://doi.org/10.3390/diagnostics11010036.

Article  PubMed  PubMed Central  Google Scholar 

Eertink JJ, van de Brug T, Wiegers SE, Zwezerijnen GJC, Pfaehler EAG, Lugtenburg PJ, et al. (18)F-FDG PET baseline radiomics features improve the prediction of treatment outcome in diffuse large B-cell lymphoma. Eur J Nucl Med Mol Imaging. 2022;49:932–42. https://doi.org/10.1007/s00259-021-05480-3.

Article  PubMed  Google Scholar 

Zhang X, Chen L, Jiang H, He X, Feng L, Ni M, et al. A novel analytic approach for outcome prediction in diffuse large B-cell lymphoma by [(18)F]FDG PET/CT. Eur J Nucl Med Mol Imaging. 2022;49:1298–310. https://doi.org/10.1007/s00259-021-05572-0.

Article  CAS  PubMed  Google Scholar 

Frood R, Clark M, Burton C, Tsoumpas C, Frangi AF, Gleeson F, et al. Discovery of pre-treatment FDG PET/CT-derived radiomics-based models for predicting outcome in diffuse large B-Cell lymphoma. Cancers (Basel). 2022. https://doi.org/10.3390/cancers14071711.

Article  PubMed  PubMed Central  Google Scholar 

Nioche C, Orlhac F, Boughdad S, Reuze S, Goya-Outi J, Robert C, et al. LIFEx: a freeware for radiomic feature calculation in multimodality imaging to accelerate advances in the characterization of tumor heterogeneity. Cancer Res. 2018;78:4786–9. https://doi.org/10.1158/0008-5472.CAN-18-0125.

Article  CAS  PubMed  Google Scholar 

Barrington SF, Zwezerijnen B, de Vet HCW, Heymans MW, Mikhaeel NG, Burggraaff CN, et al. Automated segmentation of baseline metabolic total tumor burden in diffuse large b-cell lymphoma: which method is most successful? A study on behalf of the PETRA consortium. J Nucl Med. 2021;62:332–7. https://doi.org/10.2967/jnumed.119.238923.

Article  CAS  PubMed  PubMed Central  Google Scholar 

van Griethuysen JJM, Fedorov A, Parmar C, Hosny A, Aucoin N, Narayan V, et al. Computational radiomics system to decode the radiographic phenotype. Cancer Res. 2017;77:e104–7. https://doi.org/10.1158/0008-5472.CAN-17-0339.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Mu W, Schabath MB, Gillies RJ. Images are data: challenges and opportunities in the clinical translation of radiomics. Cancer Res. 2022;82:2066–8. https://doi.org/10.1158/0008-5472.CAN-22-1183.

Article  CAS  PubMed  Google Scholar 

Hatt M, Krizsan AK, Rahmim A, Bradshaw TJ, Costa PF, Forgacs A, et al. Joint EANM/SNMMI guideline on radiomics in nuclear medicine: jointly supported by the EANM physics committee and the SNMMI physics, instrumentation and data sciences council. Eur J Nucl Med Mol Imaging. 2023;50:352–75. https://doi.org/10.1007/s00259-022-06001-6.

Article  CAS  PubMed  Google Scholar 

Tibshirani R. The lasso method for variable selection in the Cox model. Stat Med. 1997;16:385–95.

Article  CAS  PubMed  Google Scholar 

A New Look at the Statistical Model Identification.pdf.

Lu Y, Yu J, Gong W, Su L, Sun X, Bai O, et al. An immune-clinical prognostic index (ICPI) for patients with de novo follicular lymphoma treated With R-CHOP/CHOP chemotherapy. Front Oncol. 2021;11: 708784. https://doi.org/10.3389/fonc.2021.708784.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Beukinga RJ, Hulshoff JB, Mul VEM, Noordzij W, Kats-Ugurlu G, Slart R, et al. Prediction of response to neoadjuvant chemotherapy and radiation therapy with baseline and restaging (18)F-FDG PET imaging biomarkers in patients with esophageal cancer. Radiology. 2018;287:983–92. https://doi.org/10.1148/radiol.2018172229.

Article  PubMed  Google Scholar 

DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics. 1988;44:837–45.

Article  CAS  PubMed  Google Scholar 

Aide N, Fruchart C, Nganoa C, Gac AC, Lasnon C. Baseline (18)F-FDG PET radiomic features as predictors of 2-year event-free survival in diffuse large B cell lymphomas treated with immunochemotherapy. Eur Radiol. 2020;30:4623–32. https://doi.org/10.1007/s00330-020-06815-8.

Article  PubMed  Google Scholar 

Jiang C, Li A, Teng Y, Huang X, Ding C, Chen J, et al. Optimal PET-based radiomic signature construction based on the cross-combination method for predicting the survival of patients with diffuse large B-cell lymphoma. Eur J Nucl Med Mol Imaging. 2022;49:2902–16. https://doi.org/10.1007/s00259-022-05717-9.

Article  PubMed  Google Scholar 

Sala E, Mema E, Himoto Y, Veeraraghavan H, Brenton JD, Snyder A, et al. Unravelling tumour heterogeneity using next-generation imaging: radiomics, radiogenomics, and habitat imaging. Clin Radiol. 2017;72:3–10. https://doi.org/10.1016/j.crad.2016.09.013.

Article  CAS  PubMed  Google Scholar