FDG PET/CT radiomics for predicting the outcome of locally advanced rectal cancer
- 1.3k Downloads
The aim of this study was to investigate the prognostic value of baseline 18F-FDG PET/CT textural analysis in locally-advanced rectal cancer (LARC).
Eighty-six patients with LARC underwent 18F-FDG PET/CT before treatment. Maximum and mean standard uptake values (SUVmax and SUVmean), metabolic tumoral volume (MTV), total lesion glycolysis (TLG), histogram-intensity features, as well as 11 local and regional textural features, were evaluated. The relationships of clinical, pathological and PET-derived metabolic parameters with disease-specific survival (DSS), disease-free survival (DFS) and overall survival (OS) were assessed by Cox regression analysis. Logistic regression was used to predict the pathological response by the Dworak tumor regression grade (TRG) in the 66 patients treated with neoadjuvant chemoradiotherapy (nCRT).
The median follow-up of patients was 41 months. Seventeen patients (19.7%) had recurrent disease and 18 (20.9 %) died, either due to cancer progression (n = 10) or from another cause while in complete remission (n = 8). DSS was 95% at 1 year, 93% at 2 years and 87% at 4 years. Weight loss, surgery and the texture parameter coarseness were significantly associated with DSS in multivariate analyses. DFS was 94 % at 1 year, 86 % at 2 years and 79 % at 4 years. From a multivariate standpoint, tumoral differentiation and the texture parameters homogeneity and coarseness were significantly associated with DFS. OS was 93% at 1 year, 87% at 2 years and 79% after 4 years. cT, surgery, SUVmean, dissimilarity and contrast from the neighborhood intensity-difference matrix (contrastNGTDM) were significantly and independently associated with OS. Finally, RAS-mutational status (KRAS and NRAS mutations) and TLG were significant predictors of pathological response to nCRT (TRG 3-4).
Textural analysis of baseline 18F-FDG PET/CT provides strong independent predictors of survival in patients with LARC, with better predictive power than intensity- and volume-based parameters. The utility of such features, especially coarseness, should be confirmed by larger clinical studies before considering their potential integration into decisional algorithms aimed at personalized medicine.
Keywords18F-FDG PET/CT Textural analysis Tumor heterogeneity Radiomics Rectal cancer
We thank our colleague André Frère, from the department of Gastro-enterology of the CHR of Liege, who granted us access to data from patients followed in his hospital, Sébastien Jodogne, from the department of Medical Physics of the CHU of Liege, for the design of the textural analysis software, and Stéphanie Gofflot, from the Biobank of the University of Liege, for providing tumoral samples for genetic analyzes.
Compliance with ethical standards
Conflicts of interest
All procedures were performed in accordance with the principles of the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. The study design and exemption from informed consent were approved by the Institutional Review Board of Liege University Hospital.
For this type of study formal consent is not required.
- 2.NCCN Guidelines version 3.2017 Rectal Cancer. https://www.nccn.org/professionals/physician_gls/pdf/rectal.pdf.
- 3.Compton CC, Fielding LP, Burgart LJ, Conley B, Cooper HS, Hamilton SR, et al. Prognostic factors in colorectal cancer. College of American Pathologists Consensus Statement 1999. Arch Pathol Lab Med. 2000;124(7):979–94. https://doi.org/10.1043/0003-9985(2000)124<0979:PFICC>2.0.CO;2.PubMedGoogle Scholar
- 4.Taylor FG, Quirke P, Heald RJ, Moran BJ, Blomqvist L, Swift IR, et al. Preoperative magnetic resonance imaging assessment of circumferential resection margin predicts disease-free survival and local recurrence: 5-year follow-up results of the MERCURY study. J Clin Oncol. 2014;32(1):34–43. https://doi.org/10.1200/JCO.2012.45.3258.CrossRefPubMedGoogle Scholar
- 5.Ng F, Ganeshan B, Kozarski R, Miles KA, Goh V. Assessment of primary colorectal cancer heterogeneity by using whole-tumor texture analysis: contrast-enhanced CT texture as a biomarker of 5-year survival. Radiology. 2013;266(1):177–84. https://doi.org/10.1148/radiol.12120254.CrossRefPubMedGoogle Scholar
- 8.Kim SJ, Chang S. Volumetric parameters changes of sequential 18F-FDG PET/CT for early prediction of recurrence and death in patients with locally advanced rectal cancer treated with preoperative chemoradiotherapy. Clin Nucl Med. 2015;40(12):930–5. https://doi.org/10.1097/RLU.0000000000000917.CrossRefPubMedGoogle Scholar
- 9.Ruby JA, Leibold T, Akhurst TJ, Shia J, Saltz LB, Mazumdar M, et al. FDG-PET assessment of rectal cancer response to neoadjuvant chemoradiotherapy is not associated with long-term prognosis: a prospective evaluation. Dis Colon Rectum. 2012;55(4):378–86. https://doi.org/10.1097/DCR.0b013e318244a666.CrossRefPubMedGoogle Scholar
- 15.Joye I, Deroose CM, Vandecaveye V, Haustermans K. The role of diffusion-weighted MRI and (18)F-FDG PET/CT in the prediction of pathologic complete response after radiochemotherapy for rectal cancer: a systematic review. Radiother Oncol. 2014;113(2):158–65. https://doi.org/10.1016/j.radonc.2014.11.026.CrossRefPubMedGoogle Scholar
- 17.Li QW, Zheng RL, Ling YH, Wang QX, Xiao WW, Zeng ZF, et al. Prediction of tumor response after neoadjuvant chemoradiotherapy in rectal cancer using (18)fluorine-2-deoxy-D-glucose positron emission tomography-computed tomography and serum carcinoembryonic antigen: a prospective study. Abdom Radiol (NY). 2016;41(8):1448–55. https://doi.org/10.1007/s00261-016-0698-7.CrossRefGoogle Scholar
- 18.van Stiphout RG, Valentini V, Buijsen J, Lammering G, Meldolesi E, van Soest J, et al. Nomogram predicting response after chemoradiotherapy in rectal cancer using sequential PETCT imaging: a multicentric prospective study with external validation. Radiother Oncol. 2014;113(2):215–22. https://doi.org/10.1016/j.radonc.2014.11.002.CrossRefPubMedGoogle Scholar
- 19.Leccisotti L, Gambacorta MA, de Waure C, Stefanelli A, Barbaro B, Vecchio FM, et al. The predictive value of 18F-FDG PET/CT for assessing pathological response and survival in locally advanced rectal cancer after neoadjuvant radiochemotherapy. Eur J Nucl Med Mol Imaging. 2015;42(5):657–66. https://doi.org/10.1007/s00259-014-2820-9.CrossRefPubMedGoogle Scholar
- 22.Rymer B, Curtis NJ, Siddiqui MR, Chand M. FDG PET/CT can assess the response of locally advanced rectal cancer to neoadjuvant chemoradiotherapy: evidence from meta-analysis and systematic review. Clin Nucl Med. 2016;41(5):371–5. https://doi.org/10.1097/RLU.0000000000001166.CrossRefPubMedGoogle Scholar
- 27.Tixier F, Le Rest CC, Hatt M, Albarghach N, Pradier O, Metges JP, et al. Intratumor heterogeneity characterized by textural features on baseline 18F-FDG PET images predicts response to concomitant radiochemotherapy in esophageal cancer. J Nucl Med. 2011;52(3):369–78. https://doi.org/10.2967/jnumed.110.082404.CrossRefPubMedPubMedCentralGoogle Scholar
- 28.Cheng NM, Fang YH, Chang JT, Huang CG, Tsan DL, Ng SH, et al. Textural features of pretreatment 18F-FDG PET/CT images: prognostic significance in patients with advanced T-stage oropharyngeal squamous cell carcinoma. J Nucl Med. 2013;54(10):1703–9. https://doi.org/10.2967/jnumed.112.119289.CrossRefPubMedGoogle Scholar
- 29.Cook GJ, Yip C, Siddique M, Goh V, Chicklore S, Roy A, et al. Are pretreatment 18F-FDG PET tumor textural features in non-small cell lung cancer associated with response and survival after chemoradiotherapy? J Nucl Med. 2013;54(1):19–26. https://doi.org/10.2967/jnumed.112.107375.CrossRefPubMedGoogle Scholar
- 30.Hatt M, Majdoub M, Vallieres M, Tixier F, Le Rest CC, Groheux D, et al. 18F-FDG PET uptake characterization through texture analysis: investigating the complementary nature of heterogeneity and functional tumor volume in a multi-cancer site patient cohort. J Nucl Med. 2015;56(1):38–44. https://doi.org/10.2967/jnumed.114.144055.CrossRefPubMedGoogle Scholar
- 31.Lovinfosse P, Janvary ZL, Coucke P, Jodogne S, Bernard C, Hatt M, et al. FDG PET/CT texture analysis for predicting the outcome of lung cancer treated by stereotactic body radiation therapy. Eur J Nucl Med Mol Imaging. 2016;43(8):1453–60. https://doi.org/10.1007/s00259-016-3314-8.CrossRefPubMedGoogle Scholar
- 32.Bundschuh RA, Dinges J, Neumann L, Seyfried M, Zsoter N, Papp L, et al. Textural parameters of tumor heterogeneity in (1)(8)F-FDG PET/CT for therapy response assessment and prognosis in patients with locally advanced rectal cancer. J Nucl Med. 2014;55(6):891–7. https://doi.org/10.2967/jnumed.113.127340.CrossRefPubMedGoogle Scholar
- 33.Bang JI, Ha S, Kang SB, Lee KW, Lee HS, Kim JS, et al. Prediction of neoadjuvant radiation chemotherapy response and survival using pretreatment [(18)F]FDG PET/CT scans in locally advanced rectal cancer. Eur J Nucl Med Mol Imaging. 2016;43(3):422–31. https://doi.org/10.1007/s00259-015-3180-9.CrossRefPubMedGoogle Scholar
- 35.Hatt M, Cheze-le Rest C, van Baardwijk A, Lambin P, Pradier O, Visvikis D. Impact of tumor size and tracer uptake heterogeneity in (18)F-FDG PET and CT non-small cell lung cancer tumor delineation. J Nucl Med. 2011;52(11):1690–7. https://doi.org/10.2967/jnumed.111.092767.CrossRefPubMedPubMedCentralGoogle Scholar
- 37.Haralick R, Shanmugam K, Dinstein I. Textural features for image classification. IEEE Trans Syst Man Cybern. 1973:610–21.Google Scholar
- 41.Desseroit MC, Tixier F, Weber WA, Siegel BA, Cheze Le Rest C, Visvikis D, et al. Reliability of PET/CT shape and heterogeneity features in functional and morphological components of non-small cell lung cancer tumors: a repeatability analysis in a prospective multi-center cohort. J Nucl Med. 2017;58(3):406–11. https://doi.org/10.2967/jnumed.116.180919. CrossRefPubMedPubMedCentralGoogle Scholar
- 42.Van Velden FH, Kramer GM, Frings V, Nissen IA, Mulder ER, de Langen AJ, et al. Repeatability of radiomic features in non-small-cell lung cancer [(18)F]FDG-PET/CT studies: impact of reconstruction and delineation. Mol Imaging Biol. 2016;18(5):788–95. https://doi.org/10.1007/s11307-016-0940-2.CrossRefPubMedPubMedCentralGoogle Scholar
- 43.Lu L, Lv W, Jiang J, Ma J, Feng Q, Rahmim A, et al. Robustness of radiomic features in [11C]Choline and [18F]FDG PET/CT imaging of nasopharyngeal carcinoma: impact of segmentation and discretization. Mol Imaging Biol. 2016;18(6):935–45. https://doi.org/10.1007/s11307-016-0973-6.CrossRefPubMedGoogle Scholar
- 46.Pyka T, Bundschuh RA, Andratschke N, Mayer B, Specht HM, Papp L, et al. Textural features in pre-treatment [F18]-FDG-PET/CT are correlated with risk of local recurrence and disease-specific survival in early stage NSCLC patients receiving primary stereotactic radiation therapy. Radiat Oncol. 2015;10:100. https://doi.org/10.1186/s13014-015-0407-7.CrossRefPubMedPubMedCentralGoogle Scholar
- 47.JS O, Kang BC, Roh JL, Kim JS, Cho KJ, Lee SW, et al. Intratumor textural heterogeneity on pretreatment (18)F-FDG PET images predicts response and survival after chemoradiotherapy for hypopharyngeal cancer. Ann Surg Oncol. 2015;22(8):2746–54. https://doi.org/10.1245/s10434-014-4284-3.CrossRefGoogle Scholar
- 48.van Rossum PS, Fried DV, Zhang L, Hofstetter WL, van Vulpen M, Meijer GJ, et al. The incremental vValue of subjective and quantitative assessment of 18F-FDG PET for the prediction of pathologic complete response to preoperative chemoradiotherapy in esophageal cancer. J Nucl Med. 2016;57(5):691–700. https://doi.org/10.2967/jnumed.115.163766.CrossRefPubMedGoogle Scholar
- 50.Pyka T, Gempt J, Hiob D, Ringel F, Schlegel J, Bette S, et al. Textural analysis of pre-therapeutic [18F]-FET-PET and its correlation with tumor grade and patient survival in high-grade gliomas. Eur J Nucl Med Mol Imaging. 2016;43(1):133–41. https://doi.org/10.1007/s00259-015-3140-4.CrossRefPubMedGoogle Scholar
- 53.Maffione AM, Ferretti A, Grassetto G, Bellan E, Capirci C, Chondrogiannis S, et al. Fifteen different 18F-FDG PET/CT qualitative and quantitative parameters investigated as pathological response predictors of locally advanced rectal cancer treated by neoadjuvant chemoradiation therapy. Eur J Nucl Med Mol Imaging. 2013;40(6):853–64. https://doi.org/10.1007/s00259-013-2357-3.CrossRefPubMedGoogle Scholar
- 54.Dos Anjos DA, Perez RO, Habr-Gama A, Sao Juliao GP, Vailati BB, Fernandez LM, et al. Semiquantitative volumetry by sequential PET/CT may improve prediction of complete response to neoadjuvant chemoradiation in patients with distal rectal cancer. Dis Colon Rectum. 2016;59(9):805–12. https://doi.org/10.1097/DCR.0000000000000655.CrossRefPubMedGoogle Scholar
- 58.Duldulao MP, Lee W, Nelson RA, Li W, Chen Z, Kim J, et al. Mutations in specific codons of the KRAS oncogene are associated with variable resistance to neoadjuvant chemoradiation therapy in patients with rectal adenocarcinoma. Ann Surg Oncol. 2013;20(7):2166–71. https://doi.org/10.1245/s10434-013-2910-0.CrossRefPubMedPubMedCentralGoogle Scholar
- 59.Chow OS, Kuk D, Keskin M, Smith JJ, Camacho N, Pelossof R, et al. KRAS and combined KRAS/TP53 mutations in locally advanced rectal cancer are independently associated with decreased response to neoadjuvant therapy. Ann Surg Oncol. 2016;23(8):2548–55. https://doi.org/10.1245/s10434-016-5205-4.CrossRefPubMedPubMedCentralGoogle Scholar