What does radiomics do in PD-L1 blockade therapy of NSCLC patients?

被引:5
作者
Cui, Ruichen
Yang, Zhenyu
Liu, Lunxu [1 ,2 ]
机构
[1] Sichuan Univ, West China Hosp, Inst Thorac Oncol, 37 Guoxue Alley, Chengdu 610041, Sichuan, Peoples R China
[2] Sichuan Univ, West China Hosp, Dept Thorac Surg, 37 Guoxue Alley, Chengdu 610041, Sichuan, Peoples R China
关键词
features; non-small cell lung cancer; prediction; programmed cell death 1 ligand 1; radiomics; CELL LUNG-CANCER; IMMUNE CHECKPOINT INHIBITORS; CLINICAL-OUTCOMES; PROGNOSTIC VALUE; FDG-PET; EXPRESSION; FEATURES; IMMUNOTHERAPY; RECEPTOR; IMAGES;
D O I
10.1111/1759-7714.14620
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
With the in-depth understanding of programmed cell death 1 ligand 1 (PD-L1) in non-small cell lung cancer (NSCLC), PD-L1 has become a vital immunotherapy target and a significant biomarker. The clinical utility of detecting PD-L1 by immunohistochemistry or next-generation sequencing has been written into guidelines. However, the application of these methods is limited in some circumstances where the biopsy size is small or not accessible, or a dynamic monitor is needed. Radiomics can noninvasively, in real-time, and quantitatively analyze medical images to reflect deeper information about diseases. Since radiomics was proposed in 2012, it has been widely used in disease diagnosis and differential diagnosis, tumor staging and grading, gene and protein phenotype prediction, treatment plan decision-making, efficacy evaluation, and prognosis prediction. To explore the feasibility of the clinical application of radiomics in predicting PD-L1 expression, immunotherapy response, and long-term prognosis, we comprehensively reviewed and summarized recently published works in NSCLC. In conclusion, radiomics is expected to be a companion to the whole immunotherapy process.
引用
收藏
页码:2669 / 2680
页数:12
相关论文
共 117 条
  • [1] Radiomics for Predicting Response to First-Line Anti-PD1 Therapy in Advanced NSCLC
    Ackermann, C.
    Fornacon-Wood, I.
    Tay, R.
    Manoharan, P.
    Price, G.
    Lindsay, C.
    Faivre-Finn, C.
    Blackhall, F.
    Cobben, D.
    [J]. JOURNAL OF THORACIC ONCOLOGY, 2019, 14 (10) : S457 - S458
  • [2] QUANTITATIVE LUNG AIRWAY MORPHOLOGY (QUALM) FEATURES ON CHEST CT SCANS ARE ASSOCIATED WITH RESPONSE AND OVERALL SURVIVAL IN LUNG CANCER PATIENTS TREATED WITH CHECKPOINT INHIBITORS
    Alilou, Mehdi
    Patton, Thomas
    Patil, Pradnya
    Pennell, Nathan
    Bera, Kaustav
    Gupta, Amit
    Fu, Pingfu
    Velcheti, Vamsidhar
    Madabhushi, Anant
    [J]. JOURNAL FOR IMMUNOTHERAPY OF CANCER, 2021, 9 : A44 - A44
  • [3] An integrated segmentation and shape-based classification scheme for distinguishing adenocarcinomas from granulomas on lung CT
    Alilou, Mehdi
    Beig, Niha
    Orooji, Mahdi
    Rajiah, Prabhakar
    Velcheti, Vamsidhar
    Rakshit, Sagar
    Reddy, Niyoti
    Yang, Michael
    Jacono, Frank
    Gilkeson, Robert C.
    Linden, Philip
    Madabhushi, Anant
    [J]. MEDICAL PHYSICS, 2017, 44 (07) : 3556 - 3569
  • [4] Cancer cachexia: understanding the molecular basis
    Argiles, Josep M.
    Busquets, Silvia
    Stemmler, Britta
    Lopez-Soriano, Francisco J.
    [J]. NATURE REVIEWS CANCER, 2014, 14 (11) : 754 - 762
  • [5] Cancer-associated cachexia
    Baracos, Vickie E.
    Martin, Lisa
    Korc, Murray
    Guttridge, Denis C.
    Fearon, Kenneth C. H.
    [J]. NATURE REVIEWS DISEASE PRIMERS, 2018, 4
  • [6] Artificial intelligence in cancer imaging: Clinical challenges and applications
    Bi, Wenya Linda
    Hosny, Ahmed
    Schabath, Matthew B.
    Giger, Maryellen L.
    Birkbak, Nicolai J.
    Mehrtash, Alireza
    Allison, Tavis
    Arnaout, Omar
    Abbosh, Christopher
    Dunn, Ian F.
    Mak, Raymond H.
    Tamimi, Rulla M.
    Tempany, Clare M.
    Swanton, Charles
    Hoffmann, Udo
    Schwartz, Lawrence H.
    Gillies, Robert J.
    Huang, Raymond Y.
    Aerts, Hugo J. W. L.
    [J]. CA-A CANCER JOURNAL FOR CLINICIANS, 2019, 69 (02) : 127 - 157
  • [7] Radiomics and artificial intelligence in lung cancer screening
    Binczyk, Franciszek
    Prazuch, Wojciech
    Bozek, Pawel
    Polanska, Joanna
    [J]. TRANSLATIONAL LUNG CANCER RESEARCH, 2021, 10 (02) : 1186 - 1199
  • [8] Quantitative CT texture analysis in predicting PD-L1 expression in locally advanced or metastatic NSCLC patients
    Bracci, Stefano
    Dolciami, Miriam
    Trobiani, Claudio
    Izzo, Antonella
    Pernazza, Angelina
    D'Amati, Giulia
    Manganaro, Lucia
    Ricci, Paolo
    [J]. RADIOLOGIA MEDICA, 2021, 126 (11): : 1425 - 1433
  • [9] Management of Immune-Related Adverse Events in Patients Treated With Immune Checkpoint Inhibitor Therapy: American Society of Clinical Oncology Clinical Practice Guideline
    Brahmer, Julie R.
    Lacchetti, Christina
    Schneider, Bryan J.
    Atkins, Michael B.
    Brassil, Kelly J.
    Caterino, Jeffrey M.
    Chau, Ian
    Ernstoff, Marc S.
    Gardner, Jennifer M.
    Ginex, Pamela
    Hallmeyer, Sigrun
    Chakrabarty, Jennifer Holter
    Leighl, Natasha B.
    Mammen, Jennifer S.
    McDermott, David F.
    Naing, Aung
    Nastoupil, Loretta J.
    Phillips, Tanyanika
    Porter, Laura D.
    Puzanov, Igor
    Reichner, Cristina A.
    Santomasso, Bianca D.
    Seigel, Carole
    Spira, Alexander
    Suarez-Almazor, Maria E.
    Wang, Yinghong
    Weber, Jeffrey S.
    Wolchok, Jedd D.
    Thompson, John A.
    [J]. JOURNAL OF CLINICAL ONCOLOGY, 2018, 36 (17) : 1714 - +
  • [10] Programmed death-1 ligand 1 interacts specifically with the B7-1 costimulatory molecule to inhibit T cell responses
    Butte, Manish J.
    Keir, Mary E.
    Phamduy, Theresa B.
    Sharpe, Arlene H.
    Freeman, Gordon J.
    [J]. IMMUNITY, 2007, 27 (01) : 111 - 122