A clinical-radiomic model for improved prognostication of surgical candidates with colorectal liver metastases.
colorectal cancer
computed tomography
magnetic resonance imaging
radiomics
Journal
Journal of surgical oncology
ISSN: 1096-9098
Titre abrégé: J Surg Oncol
Pays: United States
ID NLM: 0222643
Informations de publication
Date de publication:
Feb 2020
Feb 2020
Historique:
received:
13
11
2019
accepted:
17
11
2019
pubmed:
5
12
2019
medline:
5
12
2019
entrez:
5
12
2019
Statut:
ppublish
Résumé
Colorectal cancer with liver metastases is potentially curable with surgical resection however clinical prognostic factors can insufficiently stratify patients. This study aims to assess whether radiomic features are prognostic and can inform clinical decision making. This single-site retrospective study included 102 patients who underwent colorectal liver metastases resection with preoperative computed tomography (CT), magnetic resonance imaging (MRI) with gadoxetic acid (EOB) and clinical covariates. A lasso-regularized multivariate Cox proportional hazards model was applied to 114 features (10 clinical, 104 radiomic) to determine association with disease-free survival (DFS). A prognostic index was derived using the significant Cox regression coefficients and their corresponding input features and a threshold was determined to classify patients into high- and low-risk groups, and DFS compared using log-rank tests. Four covariates were significantly associated with DFS; bilobar disease (hazard ratio [HR]= 1.56; P = .0043), complete pathological response (HR= 0.67; P = .025), minimum pixel value (HR= 1.66; P = .00016), and small area emphasis (HR= 0.62; P = .0013) from the EOB-MRI data. Radiomic CT features were not prognostic. The prognostic index strongly stratified high- and low-risk prognostic groups (HR = 0.31; P = .00068). Radiomic MRI features provided meaningful prognostic information above clinical covariates alone. This merits further validation for potential clinical implementation to inform management.
Sections du résumé
BACKGROUND AND OBJECTIVES
OBJECTIVE
Colorectal cancer with liver metastases is potentially curable with surgical resection however clinical prognostic factors can insufficiently stratify patients. This study aims to assess whether radiomic features are prognostic and can inform clinical decision making.
METHODS
METHODS
This single-site retrospective study included 102 patients who underwent colorectal liver metastases resection with preoperative computed tomography (CT), magnetic resonance imaging (MRI) with gadoxetic acid (EOB) and clinical covariates. A lasso-regularized multivariate Cox proportional hazards model was applied to 114 features (10 clinical, 104 radiomic) to determine association with disease-free survival (DFS). A prognostic index was derived using the significant Cox regression coefficients and their corresponding input features and a threshold was determined to classify patients into high- and low-risk groups, and DFS compared using log-rank tests.
RESULTS
RESULTS
Four covariates were significantly associated with DFS; bilobar disease (hazard ratio [HR]= 1.56; P = .0043), complete pathological response (HR= 0.67; P = .025), minimum pixel value (HR= 1.66; P = .00016), and small area emphasis (HR= 0.62; P = .0013) from the EOB-MRI data. Radiomic CT features were not prognostic. The prognostic index strongly stratified high- and low-risk prognostic groups (HR = 0.31; P = .00068).
CONCLUSION
CONCLUSIONS
Radiomic MRI features provided meaningful prognostic information above clinical covariates alone. This merits further validation for potential clinical implementation to inform management.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
357-364Informations de copyright
© 2019 Wiley Periodicals, Inc.
Références
Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68:394-424.
Manfredi S, Lepage C, Hatem C, Coatmeur O, Faivre J, Bouvier AM. Epidemiology and management of liver metastases from colorectal cancer. Ann Surg. 2006;244:254-259.
Fong Y, Fortner J, Sun RL, Brennan MF, Blumgart LH. Clinical score for predicting recurrence after hepatic resection for metastatic colorectal cancer. Ann Surg. 1999;230:309-318.
Choti MA, Sitzmann JV, Tiburi MF, et al. Trends in long-term survival following liver resection for hepatic colorectal metastases. Ann Surg. 2002;235:759-766.
Pulitanò C, Castillo F, Aldrighetti L, et al. What defines ‘cure’ after liver resection for colorectal metastases? Results after 10 years of follow-up. HPB. 2010;12:244-249.
Tomlinson JS, Jarnagin WR, DeMatteo RP, et al. Actual 10-year survival after resection of colorectal liver metastases defines cure. J Clin Oncol. 2007;25:4575-4580.
Malik HZ, Prasad KR, Halazun KJ, et al. Preoperative prognostic score for predicting survival after hepatic resection for colorectal liver metastases. Ann Surg. 2007;246:806-814.
Vauthey JN, Zimmitti G, Kopetz SE, et al. RAS mutation status predicts survival and patterns of recurrence in patients undergoing hepatectomy for colorectal liver metastases. Ann Surg. 2013;258:619-627.
Gomez D, Cameron IC. Prognostic scores for colorectal liver metastasis: clinically important or an academic exercise? HPB. 2010;12:227-238.
Muhi A, Ichikawa T, Motosugi U, et al. Diagnosis of colorectal hepatic metastases: comparison of contrast-enhanced CT, contrast-enhanced US, superparamagnetic iron oxide-enhanced MRI and gadoxetic acid-enhanced MRI. J Magn Reson Imaging. 2011;34:326-335.
Halavaara J, Breuer J, Ayuso C, et al. Liver tumor characterization: comparison between liver-specific gadoxetic acid disodium-enhanced MRI and biphasic CT: a multicenter trial. J Comput Assist Tomogr. 2006;30:345-354.
Zech CJ, Korpraphong P, Huppertz A, et al. Randomized multicentre trial of gadoxetic acid-enhanced MRI versus conventional MRI or CT in the staging of colorectal cancer liver metastases. Br J Surg. 2014;101:613-621.
Lee KH, Lee JM, Park JH, et al. MR imaging in patients with suspected liver metastases: value of liver-specific contrast agent gadoxetic acid. Korean J Radiol. 2013;14:894-904.
Sofue K, Tsurusaki M, Murakami T, et al. Does gadoxetic acid-enhanced 3.0T MRI in addition to 64-detector-row contrast-enhanced CT provide better diagnostic performance and change the therapeutic strategy for the preoperative evaluation of colorectal liver metastases? Eur Radiol. 2014;24:2532-2539.
Gillies RJ, Kinahan PE, Hricak H. Radiomics: images are more than pictures, they are data. Radiology. 2016;278:563-577.
Rubbia-Brandt L, Giostra E, Brezault C, et al. Importance of histological tumor response assessment in predicting the outcome in patients with colorectal liver metastases treated with neo-adjuvant chemotherapy followed by liver surgery. Ann Oncol. 2007;18:299-304.
Boonsirikamchai P, Asran MA, Maru DM, et al. CT findings of response and recurrence, independent of change in tumor size, in colorectal liver metastasis treated with bevacizumab. Am J Roentgenol. 2011;197:W1060-W1066.
Larroza A, Bodí V, Moratal D. Analysis in magnetic resonance imaging: review and considerations for future applications, assessment of cellular organ function and dysfunction using direct and derived MRI methodologies. Intech. 2016. https://doi.org/10.5772/64641
Fedorov A, Beichel R, Kalpathy-Cramer J, et al. 3D Slicer as an image computing platform for the Quantitative Imaging Network. Magn Reson Imaging. 2012;30:1323-1341.
van Griethuysen JJM, Fedorov A, Parmar C, et al. Computational radiomics system to decode the radiographic phenotype. Cancer Res. 2017;77:e104-e107.
Zwanenburg A, Leger S, Vallières M, Löck S. Image biomarker standardisation initiative. 2016. arXiv:1612.07003.
Papanikolaou N, Santinha J. An introduction to radiomics: capturing tumour biology in space and time. Hell J Radiol. 2018;3:61-71.
Kuhn M. Building predictive models in R using the caret package. J Stat Software. 2008;28:1-26.
Cox DR. Regression models and life-tables. J Royal Stat Soc. 1972;34:187-220.
Lausen B, Schumacher M. Maximally selected rank statistics. Biometrics. 1992;48:73.
Iwatsuki S, Dvorchik I, Madariaga JR, et al. Hepatic resection for metastatic colorectal adenocarcinoma: a proposal of a prognostic scoring system. J Am Coll Surg. 1999;189:291-299.
Nordlinger B, Guiguet M, Vaillant JC, et al. Surgical resection of colorectal carcinoma metastases to the liver: A prognostic scoring system to improve case selection, based on 1568 patients. Cancer. 1996;77:1254-1262.
Homayounfar K, Bleckmann A, Conradi LC, et al. Bilobar spreading of colorectal liver metastases does not significantly affect survival after R0 resection in the era of interdisciplinary multimodal treatment. Int J Colorectal Dis. 2012;27:1359-1367.
Chua TC, Saxena A, Liauw W, Kokandi A, Morris DL. Systematic review of randomized and nonrandomized trials of the clinical response and outcomes of neoadjuvant systemic chemotherapy for resectable colorectal liver metastases. Ann Surg Oncol. 2010;17:492-501.
Alberts SR, Horvath WL, Sternfeld WC, et al. Oxaliplatin, fluorouracil, and leucovorin for patients with unresectable liver-only metastases from colorectal cancer: a north central cancer treatment group phase II study. J Clin Oncol. 2005;23:9243-9249.
Simpson AL, Doussot A, Creasy JM, et al. Computed tomography image texture: a noninvasive prognostic marker of hepatic recurrence after hepatectomy for metastatic colorectal cancer. Ann Surg Oncol. 2017;24:2482-2490.
Miles KA, Ganeshan B, Griffiths MR, Young RC, Chatwin CR. Colorectal cancer: texture analysis of portal phase hepatic CT images as a potential marker of survival. Radiology. 2009;250:444-452.
Ravanelli M, Agazzi GM, Tononcelli E, et al. Texture features of colorectal liver metastases on pretreatment contrast-enhanced CT may predict response and prognosis in patients treated with bevacizumab-containing chemotherapy: a pilot study including comparison with standard chemotherapy. Radiol Med. 2019;124:877-886.
Dohan A, Gallix B, Guiu B, et al. Early evaluation using a radiomic signature of unresectable hepatic metastases to predict outcome in patients with colorectal cancer treated with FOLFIRI and bevacizumab. [published online ahead of print May 17, 2019]. Gut. https://doi.org/10.1136/gutjnl-2018-316407
Rao SX, Lambregts DMJ, Schnerr RS, et al. CT texture analysis in colorectal liver metastases: a better way than size and volume measurements to assess response to chemotherapy? United European Gastroenterol J. 2016;4:257-263.
Ahn SJ, Kim JH, Park SJ, Han JK. Prediction of the therapeutic response after FOLFOX and FOLFIRI treatment for patients with liver metastasis from colorectal cancer using computerized CT texture analysis. Eur J Radiol. 2016;85:1867-1874.
Beckers RCJ, Lambregts DMJ, Schnerr RS, et al. Whole liver CT texture analysis to predict the development of colorectal liver metastases-A multicentre study. Eur J Radiol. 2017;92:64-71.
Lubner MG, Stabo N, Lubner SJ, et al. CT textural analysis of hepatic metastatic colorectal cancer: pre-treatment tumor heterogeneity correlates with pathology and clinical outcomes. Abdom Imaging. 2015;40:2331-2337.
National Comprehensive Cancer Network. Clinical practice guidelines in oncology. Colon Cancer (Version 22019) n.d. https://www.nccn.org/professionals/physician_gls/pdf/colon.pdf. Accessed July 19, 2019.
Omichi K, Shindoh J, Cloyd JM, et al. Liver resection is justified for patients with bilateral multiple colorectal liver metastases: a propensity-score-matched analysis. Eur J Surg Oncol. 2018;44:122-129.
Cheung HMC, Karanicolas PJ, Hsieh E, et al. Late gadolinium enhancement of colorectal liver metastases post-chemotherapy is associated with tumour fibrosis and overall survival post-hepatectomy. Eur Radiol. 2018;28:3505-3512.
Chang HH, Leeper WR, Chan G, Quan D, Driman DK. Infarct-like necrosis: a distinct form of necrosis seen in colorectal carcinoma liver metastases treated with perioperative chemotherapy. Am J Surg Pathol. 2012;36:570-576.
Cheung HMC, Karanicolas PJ, Coburn N, Law C, Milot L. Tumor enhancement of colorectal liver metastases on preoperative gadobutrol-enhanced MRI at 5 minutes post-contrast injection is associated with overall survival post-hepatectomy. Quant Imaging Med Surg. 2019;9:312-317.
Cheung HMC, Karanicolas PJ, Coburn N, Seth V, Law C, Milot L. Delayed tumour enhancement on gadoxetate-enhanced MRI is associated with overall survival in patients with colorectal liver metastases. Eur Radiol. 2019;29:1032-1038.
Milot L, Guindi M, Gallinger S, et al. MR imaging correlates of intratumoral tissue types within colorectal liver metastases: a high-spatial-resolution fresh ex vivo radiologic-pathologic correlation study. Radiology. 2010;254:747-754.
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;266:177-184.
Reimer RP, Reimer P, Mahnken AH. Assessment of therapy response to transarterial radioembolization for liver metastases by means of post-treatment MRI-based texture analysis. Cardiovasc Intervent Radiol. 2018;41:1545-1556.
Liang HY, Huang YQ, Yang ZX, Ying-Ding, Zeng MS, Rao SX. Potential of MR histogram analyses for prediction of response to chemotherapy in patients with colorectal hepatic metastases. Eur Radiol. 2016;26:2009-2018.
Zhang H, Li W, Hu F, Sun Y, Hu T, Tong T. MR texture analysis: potential imaging biomarker for predicting the chemotherapeutic response of patients with colorectal liver metastases. Abdom Radiol. 2019;44:65-71.