Top

European Radiology

Published in:

01-07-2016 | Magnetic Resonance

Potential of MR histogram analyses for prediction of response to chemotherapy in patients with colorectal hepatic metastases

Authors: He-Yue Liang, Ya-Qin Huang, Zhao-Xia Yang, Ying-Ding, Meng-Su Zeng, Sheng-Xiang Rao

Published in: European Radiology | Issue 7/2016

Abstract

Purpose

To determine if magnetic resonance imaging (MRI) histogram analyses can help predict response to chemotherapy in patients with colorectal hepatic metastases by using response evaluation criteria in solid tumours (RECIST1.1) as the reference standard.

Materials and methods

Standard MRI including diffusion-weighted imaging (b=0, 500 s/mm²) was performed before chemotherapy in 53 patients with colorectal hepatic metastases. Histograms were performed for apparent diffusion coefficient (ADC) maps, arterial, and portal venous phase images; thereafter, mean, percentiles (1st, 10th, 50th, 90th, 99th), skewness, kurtosis, and variance were generated. Quantitative histogram parameters were compared between responders (partial and complete response, n=15) and non-responders (progressive and stable disease, n=38). Receiver operator characteristics (ROC) analyses were further analyzed for the significant parameters.

Results

The mean, 1st percentile, 10th percentile, 50th percentile, 90th percentile, 99th percentile of the ADC maps were significantly lower in responding group than that in non-responding group (p=0.000–0.002) with area under the ROC curve (AUCs) of 0.76–0.82. The histogram parameters of arterial and portal venous phase showed no significant difference (p>0.05) between the two groups.

Conclusion

Histogram-derived parameters for ADC maps seem to be a promising tool for predicting response to chemotherapy in patients with colorectal hepatic metastases.

Key Points

• ADC histogram analyses can potentially predict chemotherapy response in colorectal liver metastases.

• Lower histogram-derived parameters (mean, percentiles) for ADC tend to have good response.

• MR enhancement histogram analyses are not reliable to predict response.

Manfredi S, Lepage C, Hatem C et al (2006) Epidemiology and management of liver metastases from colorectal cancer. Ann Surg 244(2):254–259CrossRefPubMedPubMedCentral

Sofue K, Tsurusaki M, Murakami T et al (2014) 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 24(10):2532–2539CrossRefPubMed

Scharitzer M, Ba-Ssalamah A, Ringl H et al (2013) Preoperative evaluation of colorectal liver metastases: comparison between gadoxetic acid-enhanced 3.0-T MRI and contrast-enhanced MDCT with histopathological correlation. Eur Radiol 23(8):2187–2196CrossRefPubMed

Nordlinger B, Van Cutsem E, Gruenberger T et al (2009) Combination of surgery and chemotherapy and the role of targeted agents in the treatment of patients with colorectal liver metastases: recommendations from an expert panel. Ann Oncol 20:985–992CrossRefPubMed

Bruera G, Cannita K, Giuliante F et al (2012) Effectiveness of Liver Metastasectomies in Patients With Metastatic Colorectal Cancer Treated With FIr-B/FOx Triplet Chemotherapy Plus Bevacizumab. Clin Colorectal Cancer 11(2):119–126CrossRefPubMed

Nordlinger B, Sorbye H, Glimelius B et al (2008) Perioperative chemotherapy with FOLFOX4 and surgery vs. surgery alone for resectable liver metastases from colorectal cancer (EORTC Intergroup trial 40983): a randomised controlled trial. Lancet 371:1007–1016CrossRefPubMedPubMedCentral

Lehmann K, Rickenbacher A, Weber A, Pestalozzi BC, Clavien PA (2012) Chemotherapy before liver resection of colorectal metastases: friend or foe? Ann Surg 255(2):237–247CrossRefPubMed

Robinson SM, Wilson CH, Burt AD et al (2012) Chemotherapy-Associated Liver Injury in Patients with Colorectal Liver Metastases: A Systematic Review and Meta-analysis. Ann Surg Oncol 19:4287–4299CrossRefPubMedPubMedCentral

Kneuertz PJ, Maithel SK, Staley CA, Kooby DA (2011) Chemotherapy associated liver injury: impact on surgical management of colorectal liver metastases. Ann Surg Oncol 18:181–190CrossRefPubMed

10.

Marsman HA, Van Der Pool AE, Verheij J et al (2011) Hepatic steatosis assessment with CT or MRI in patients with colorectal liver metastases after neoadjuvant chemotherapy. J Surg Oncol 104:10–16CrossRefPubMed

11.

Vauthey JN, Pawlik TM, Ribero D et al (2006) Chemotherapy regimen predicts steatohepatitis and an increase in 90-day mortality after surgery for hepatic colorectal metastases. J Clin Oncol 24:2065–2072CrossRefPubMed

12.

Anzidei M, Napoli A, Zaccagna F et al (2011) Liver Metastases From Colorectal Cancer Treated With Conventional and Antiangiogenetic Chemotherapy: Evaluation With Liver Computed Tomography Perfusion and Magnetic Resonance Diffusion-Weighted Imaging. J Comput Assist Tomogr 35:690–696CrossRefPubMed

13.

Kim DH, Kim SH, Im SA et al (2012) Intermodality comparison between 3D perfusion CT and 18F-FDG PET/CT imaging for predicting early tumor response in patients with liver metastasis after chemotherapy: Preliminary results of a prospective study. Eur J Radiol 81:3542–3550CrossRefPubMed

14.

De Bruyne S, Van Damme N, Smeets P et al (2012) Value of DCE-MRI and FDG-PET/CT in the prediction of response to preoperative chemotherapy with bevacizumab for colorectal liver metastases. Br J Cancer 106(12):1926–1933CrossRefPubMedPubMedCentral

15.

Coenegrachts K, Bols A, Haspeslagh M et al (2012) Prediction and monitoring of treatment effect using T1-weighted dynamic contrast-enhanced magnetic resonance imaging in colorectal liver metastases: Potential of whole tumour ROI and selective ROI analysis. Eur J Radiol 81:3870–3876CrossRefPubMed

16.

Cui Y, Zhang XP, Sun YS et al (2008) Apparent Diffusion Coefficient: Potential Imaging Biomarker for Prediction and Early Detection of Response to Chemotherapy in Hepatic Metastases. Radiology 248:894–900CrossRefPubMed

17.

Koh DM, Scurr E, Collins D et al (2007) Predicting response of colorectal hepatic metastasis: value of pretreatment apparent diffusion coefficients. AJR Am J Roentgenol 188:1001–1008CrossRefPubMed

18.

Kukuk GM, Murtz P, Traber F et al (2014) Diffusion-weighted imaging with acquisition of three b-values for response evaluation of neuroendocrine liver metastases undergoing selective internal radiotherapy. Eur Radiol 24(2):267–276CrossRefPubMed

19.

Filss CP, Stoffels G, Galldiks N et al (2014) Histogram analysis reveals a better delineation of tumor volume from background in 18F-FET PET compared to CBV maps in a hybrid PET–MR studie in gliomas. Nucl Inst Methods Phys Res A 734:175–178CrossRef

20.

Kim JY, Kim JK, Kim N et al (2008) CT Histogram Analysis: Differentiation of Angiomyolipoma without Visible Fat from Renal Cell Carcinoma at CT Imaging. Radiology 246:472–479CrossRefPubMed

21.

Kyriazi S, Collins DJ, Messiou C et al (2011) Metastatic Ovarian and Primary Peritoneal Cancer: Assessing Chemotherapy Response with Diffusion-weighted MR Imaging —Value of Histogram Analysis of Apparent Diffusion Coefficients. Radiology 261:182–192CrossRefPubMed

22.

Nowosielski M, Recheis W, Goebel G et al (2011) ADC histograms predict response to anti-angiogenic therapy in patients with recurrent high-grade glioma. Neuroradiology 53:291–302CrossRefPubMed

23.

Pope WB, Lai A, Mehta R et al (2011) Apparent Diffusion Coefficient Histogram Analysis Stratifies Progression-Free Survival in Newly Diagnosed Bevacizumab-Treated Glioblastoma. AJNR Am J Neuroradiol 32:882–889CrossRefPubMed

24.

Pope WB, Kim HJ, Huo J et al (2009) Recurrent Glioblastoma Multiforme: ADC Histogram Analysis Predicts Response to Bevacizumab Treatment. Radiology 252:182–189CrossRefPubMed

25.

Pope WB, Qiao XJ, Kim HJ et al (2012) Apparent diffusion coefficient histogram analysis stratifies progression-free and overall survival in patients with recurrent GBM treated with bevacizumab: a multi-center study. J Neurooncol 108:491–498CrossRefPubMedPubMedCentral

26.

Szczypiński PM, Strzelecki M, Materka A et al (2009) MaZda--a software package for image texture analysis. Comput Methods Prog Biomed 94(1):66–76CrossRef

27.

Eisenhauer EA, Therasse P, Bogaerts J et al (2009) New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur J Cancer 45(2):228–247CrossRefPubMed

28.

Lyng H, Haraldseth O, Rofstad EK (2000) Measurement of cell density and necrotic fraction in human melanoma xenografts by diffusion weighted magnetic resonance imaging. Magn Reson Med 43:828–836CrossRefPubMed

29.

Deng J, Rhee TK, Sato KT et al (2006) In vivo diffusion-weighted imaging of liver tumor necrosis in the VX2 rabbit model at 1.5 Tesla. Invest Radiol 41:410–414CrossRefPubMed

30.

Herneth AM, Guccione S, Bednarski M (2003) Apparent diffusion coefficient: a quantitative parameter for in vivo tumor characterization. Eur J Radiol 45(3):208–213CrossRefPubMed

31.

Rao SX, Chen CZ, Liu H et al (2013) Three-dimensional whole-liver perfusion magnetic resonance imaging in patients with hepatocellular carcinomas and colorectal hepatic metastases. BMC Gastroenterol 13:53CrossRefPubMedPubMedCentral

Title: Potential of MR histogram analyses for prediction of response to chemotherapy in patients with colorectal hepatic metastases
Authors: He-Yue Liang
Ya-Qin Huang
Zhao-Xia Yang
Ying-Ding
Meng-Su Zeng
Sheng-Xiang Rao
Publication date: 01-07-2016
Publisher: Springer Berlin Heidelberg
Published in: European Radiology / Issue 7/2016
Print ISSN: 0938-7994
Electronic ISSN: 1432-1084
DOI: https://doi.org/10.1007/s00330-015-4043-2

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Potential of MR histogram analyses for prediction of response to chemotherapy in patients with colorectal hepatic metastases

Abstract

Purpose

Materials and methods

Results

Conclusion

Key Points

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Purpose

Materials and methods

Results

Conclusion

Key Points

Please log in to get access to this content

Other articles of this Issue 7/2016

Impact of endobronchial coiling on segmental bronchial lumen in treated and untreated lung lobes: Correlation with changes in lung volume, clinical and pulmonary function tests

T2 black lesions on routine knee MRI: differential considerations

Multimodality imaging assessment of the deleterious role of the intraluminal thrombus on the growth of abdominal aortic aneurysm in a rat model

How often are Patients Harmed When They Visit the Computed Tomography Suite? A Multi-year Experience, in Incident Reporting, in a Large Academic Medical Center

Diffusion-weighted magnetic resonance imaging of thymoma: ability of the Apparent Diffusion Coefficient in predicting the World Health Organization (WHO) classification and the Masaoka-Koga staging system and its prognostic significance on disease-free survival

Penetrating aerodigestive injuries in the neck: a proposed CT-aided modified selective management algorithm