Prognostic value of 18F-FDG PET image-based parameters in oesophageal cancer and impact of tumour delineation methodology

Hatt, Mathieu; Visvikis, Dimitris; Albarghach, N.; Tixier, Florent; Pradier, Olivier; Rest, Catherine Cheze-Le

doi:10.1007/s00259-011-1755-7

Cited by 130 publications

(106 citation statements)

References 36 publications

(33 reference statements)

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“…18 F-FDG PET data allow a quantitative evaluation of glucose metabolism of tumor. Although a lot of previous studies have reported the clinical usefulness using SUV max and volumetric parameters, these conventional parameter-based analyses have several limitations [4,5,[11][12][13]. These parameters are classified into histogram-based parameters, so they also have the short-comings of histogram analysis.…”

Section: Patientsmentioning

confidence: 99%

Autoclustering of Non-small Cell Lung Carcinoma Subtypes on 18F-FDG PET Using Texture Analysis: A Preliminary Result

Choi

Cheon

et al. 2014

Nucl Med Mol Imaging

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Purpose Texture analysis on 18 F-fluorodeoxyglucose positron emission tomography ( 18 F-FDG PET) scan is a relatively new imaging analysis tool to evaluate metabolic heterogeneity. We analyzed the difference in textural characteristics between non-small cell lung carcinoma (NSCLC) subtypes, namely adenocarcinoma (ADC) and squamous cell carcinoma (SqCC). Methods Diagnostic 18 F-FDG PET/computed tomography (CT) scans of 30y patients (median age, 67; range, 42-88) with NSCLC (17 ADC and 13 SqCC) were retrospectively analyzed. Regions of interest were manually determined on selected transverse image containing the highest SUV value in tumors. Texture parameters were extracted by histogrambased algorithms, absolute gradient-based algorithms, runlength matrix-based algorithms, co-occurrence matrix-based algorithms, and autoregressive model-based algorithms. Twenty-four out of hundreds of texture features were selected by three algorithms: Fisher coefficient, minimization of both classification error probability and average correlation, and mutual information. Automated clustering of tumors was based on the most discriminating feature calculated by linear discriminant analysis (LDA). Each tumor subtype was determined by histopathologic examination after biopsy and surgery. Results Fifteen texture features had significant different values between ADC and SqCC. LDA with 24 automateselected texture features accurately clustered between ADC and SqCC with 0.90 linear separability. There was no high correlation between SUV max and texture parameters (|r|≤0.62). Conclusion Each subtype of NSCLC tumor has different metabolic heterogeneity. The results of this study support the potential of textural parameters on FDG PET as an imaging biomarker.

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Section: Patientsmentioning

confidence: 99%

Autoclustering of Non-small Cell Lung Carcinoma Subtypes on 18F-FDG PET Using Texture Analysis: A Preliminary Result

Choi

Cheon

et al. 2014

Nucl Med Mol Imaging

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“…Positron emission tomography/computed tomography (PET/CT) has become established in cancer imaging, and is useful for stratification during the primary staging of esophageal cancer by anatomical factors, such as tumor depth, invasion, lymph node metastasis and distant metastasis (3)(4)(5)(6)(7)(8)(9)(10). However, 18 F-fluoro-2-deoxyglucose (FDG)-PET may be used to evaluate functional factors associated with tumor activity, which depends on glucose metabolism.…”

Section: Introductionmentioning

confidence: 99%

Maximum standardized uptake value in 18F-fluoro-2-deoxyglucose positron emission tomography is associated with advanced tumor factors in esophageal cancer

Kajiwara

Hiasa

Nishina

et al. 2014

Molecular and Clinical Oncology

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Abstract. Positron emission tomography/computed tomography (PET/CT) with 18 F-fluoro-2-deoxyglucose (FDG-PET/CT) has become established in cancer imaging, and derived maximum standardized uptake values (SUVmax) add functional information regarding cancer, including esophageal squamous cell carcinoma (ESCC). The aim of the present study was to determine the clinical significance and association of tumor progression using SUVmax derived from PET/CT images in patients with ESCC. In total, 101 patients with ESCC were assessed using FDG-PET/CT and the SUVmax was then compared with the clinical backgrounds and prognoses of the patients. Endoscopic ESCC biopsy specimens were obtained in order to analyze mRNA expression relative to tumor progression. The results showed that values for SUVmax were significantly higher in patients with tumor progression factors, particularly those with lymph node metastasis. Analysis of receiver operating characteristics curves revealed an optimum SUVmax cut-off value of 10.26 for node-positive disease. Patients with SUVmax ≥10.26 had gene alterations with epithelial-mesenchymal transition (EMT) and significantly worse overall survival (P=0.0012). A higher SUVmax in patients with ESCC was associated with lymph node metastasis and a poorer prognosis. Thus, the SUVmax may reflect the potential of EMT in patients with ESCC. IntroductionEsophageal cancer is an extremely lethal gastrointestinal neoplasm that leads to >300,000 mortalities worldwide annually (1). The reason for the poor prognosis is that >50% of patients already have unresectable or metastatic disease when they are diagnosed with esophageal cancer (2). A precise evaluation of the prognosis or overall survival (OS) of patients with esophageal cancer is essential for selecting appropriate treatment. Positron emission tomography/computed tomography (PET/CT) has become established in cancer imaging, and is useful for stratification during the primary staging of esophageal cancer by anatomical factors, such as tumor depth, invasion, lymph node metastasis and distant metastasis (3-10). However, 18 F-fluoro-2-deoxyglucose (FDG)-PET may be used to evaluate functional factors associated with tumor activity, which depends on glucose metabolism.It has been previously reported that the maximum standardized uptake value (SUVmax) in patients with certain types of cancer significantly correlates with survival, prognosis and recurrence (11,12). Although the clinical significance of SUVmax in esophageal cancer has been reported (13,14), the progression of esophageal cancer in specimens of esophageal squamous cell carcinoma (ESCC) using gene analysis has not yet been assessed. Therefore we investigated whether the

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“…Some of these approaches have shown high robustness and reproducibility with PET images of variable quality (depending on factors such as scanner sensitivity and image reconstruction parameters) and tumour activity distribution characteristics, allowing physiological reproducibility limits similar to those with SUV max [13,15]. In addition, the use of these approaches has shown promising results for the use of MATV measures in the prediction and prognosis of response to therapy based on 18 F-FDG PET imaging [6,10]. However, being able to accurately determine a 3D functional tumour volume does not obviate the need for PVE correction to ensure the calculation of an accurate tumour SUV mean .…”

mentioning

confidence: 99%

“…This can be explained mostly by the limited accuracy, robustness and reproducibility of the clinically available tumour delineation tools. The shortcomings of standard threshold-based approaches for MATV, which are currently the only widely available approaches in clinical practice, have been highlighted in the literature [6,12]. They include a strong dependence on overall tumour volume and contrast.…”

mentioning

confidence: 99%

“…SUV mean corresponds to the mean activity concentration in a delineated three-dimensional (3D) functional tumour volume. The most significant issues associated with the accuracy of SUV mean determination include the precision and robustness in the delineation of the tumour functional volume used [5,6], and the important influence of PVE which is closely related to the overall tumour size. The impact of PVE becomes more significant in studies of response to therapy where the metabolically active tumour volume (MATV) may change during treatment, consequently introducing a variable influence of PVE on the calculated difference in SUV mean between the baseline and the posttreatment image.…”

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confidence: 99%

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The age of reason for FDG PET image-derived indices

Visvikis

Hatt

Tixier

et al. 2012

Eur J Nucl Med Mol Imaging

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The clinical use of PET imaging using 18 F-FDG is currently predominantly focused on diagnosis in the field of oncology. In this context, image analysis is largely based on visual interpretation and the use of simple image-derived indices, such as the maximum standardized uptake value (SUV max ), which corresponds to the voxel with the maximum activity concentration in the tumour scaled by the administered activity, patient weight and blood glucose concentration. On the other hand, during the last few years there has been increasing interest in the use of 18 F-FDG PET imaging for the prediction and monitoring of therapy response. In this context the SUV max has been also predominantly used, where differences between a pretreatment and posttreatment scan have been shown to closely correlate with clinical response to treatment in a number of different cancer models [1,2].The clear advantage of such a simplistic image-derived index is the ease of use, which has significantly contributed to its widespread application in clinical practice. SUV max is also in principle less dependent on partial volume effects (PVE) resulting from the limited spatial resolution of PET imaging [3]. On the other hand, there are a number of issues associated with its use, such as lack of robustness in terms of image noise, as well as in terms of the reconstruction algorithm and the associated corrections used during the reconstruction process. Clearly the impact of these issues can be minimized by standardization of the injection, acquisition, and image reconstruction and analysis protocols. In addition, the use of peak SUV (SUV peak ), calculated by averaging the voxel values inside a small region of interest centred on the tumour maximum activity concentration voxel, can reduce the sensitivity of SUV max to noise, although results may be sensitive to the actual definition of the ROI used to compute SUV peak [4]. However and most importantly, SUV max represents only very limited information in considering radiotracer accumulation and not considering information on the associated tumour uptake distribution or on the overall tumour functional volume. This is true even in the context of static acquisitions associated with routine whole-body 18 F-FDG PET imaging, where dynamic acquisitions, which offer the possibility, through kinetic modelling, of deriving quantitative glucose metabolic rates on a voxel-by-voxel basis, are not considered.Remaining with the context of static PET imaging, overall tumour activity accumulation can be alternatively characterized using the mean SUV (SUV mean ). SUV mean corresponds to the mean activity concentration in a delineated three-dimensional (3D) functional tumour volume. The most significant issues associated with the accuracy of SUV mean determination include the precision and robustness in the delineation of the tumour functional volume used [5,6], and the important influence of PVE which is closely related to the overall tumour size. The impact of PVE becomes more significant in studies of response to...

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Prognostic value of 18F-FDG PET image-based parameters in oesophageal cancer and impact of tumour delineation methodology

Cited by 130 publications

References 36 publications

Autoclustering of Non-small Cell Lung Carcinoma Subtypes on 18F-FDG PET Using Texture Analysis: A Preliminary Result

Autoclustering of Non-small Cell Lung Carcinoma Subtypes on 18F-FDG PET Using Texture Analysis: A Preliminary Result

Maximum standardized uptake value in 18F-fluoro-2-deoxyglucose positron emission tomography is associated with advanced tumor factors in esophageal cancer

The age of reason for FDG PET image-derived indices

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