Do clinical , histological or immunohistochemical primary tumor characteristics translate into different 18 FDG-PET / CT volumetric and heterogeneity features in stage II-III breast cancer ?

PurposeThe aim of this retrospective study was to determine if some features of baseline 18F-FDG PET images, including volume and heterogeneity, reflect clinical, histological or immunohistochemical characteristics in patients with stage II or III breast cancer (BC).MethodsIncluded in the present retrospective analysis were 171 prospectively recruited patients with stage II/III BC treated consecutively at Saint-Louis hospital. Primary tumour volumes were semiautomatically delineated on pretreatment 18F-FDG PET images. The parameters extracted included SUVmax, SUVmean, metabolically active tumour volume (MATV), total lesion glycolysis (TLG) and heterogeneity quantified using the area under the curve of the cumulative histogram and textural features. Associations between clinical/histopathological characteristics and 18F-FDG PET features were assessed using one-way analysis of variance. Areas under the ROC curves (AUC) were used to quantify the discriminative power of the features significantly associated with clinical/histopathological characteristics.ResultsT3 tumours (>5 cm) exhibited higher textural heterogeneity in 18F-FDG uptake than T2 tumours (AUC <0.75), whereas there were no significant differences in SUVmax and SUVmean. Invasive ductal carcinoma showed higher SUVmax values than invasive lobular carcinoma (p = 0.008) but MATV, TLG and textural features were not discriminative. Grade 3 tumours had higher FDG uptake (AUC 0.779 for SUVmax and 0.694 for TLG), and exhibited slightly higher regional heterogeneity (AUC 0.624). Hormone receptor-negative tumours had higher SUV values than oestrogen receptor-positive (ER-positive) and progesterone receptor-positive tumours, while heterogeneity patterns showed only low-level variation according to hormone receptor expression. HER-2 status was not associated with any of the image features. Finally, SUVmax, SUVmean and TLG significantly differed among the three phenotype subgroups (HER2-positive, triple-negative and ER-positive/HER2-negative BCs), but MATV and heterogeneity metrics were not discriminative.ConclusionSUV parameters, MATV and textural features showed limited correlations with clinical and histopathological features. The three main BC subgroups differed in terms of SUVs and TLG but not in terms of MATV and heterogeneity. None of the PET-derived metrics offered high discriminative power.

[1]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[2]  H. Yagata,et al.  Predicting the prognoses of breast carcinoma patients with positron emission tomography using 2‐deoxy‐2‐fluoro[18F]‐D‐glucose , 1998, Cancer.

[3]  Peter Bartenstein,et al.  Overexpression of Glut‐1 and increased glucose metabolism in tumors are associated with a poor prognosis in patients with oral squamous cell carcinoma , 2003, Cancer.

[4]  David L. Schwartz,et al.  Tumor Hypoxia Imaging with [F-18] Fluoromisonidazole Positron Emission Tomography in Head and Neck Cancer , 2006, Clinical Cancer Research.

[5]  Anthony Rhodes,et al.  American Society of Clinical Oncology/College of American Pathologists guideline recommendations for human epidermal growth factor receptor 2 testing in breast cancer. , 2007, Archives of pathology & laboratory medicine.

[6]  Issam El-Naqa,et al.  Exploring feature-based approaches in PET images for predicting cancer treatment outcomes , 2009, Pattern Recognit..

[7]  Christian Roux,et al.  A Fuzzy Locally Adaptive Bayesian Segmentation Approach for Volume Determination in PET , 2009, IEEE Transactions on Medical Imaging.

[8]  Yun Yen,et al.  NCCN clinical practice guidelines in oncology: hepatobiliary cancers. , 2009, Journal of the National Comprehensive Cancer Network : JNCCN.

[9]  Dimitris Visvikis,et al.  Accurate automatic delineation of heterogeneous functional volumes in positron emission tomography for oncology applications. , 2010, International journal of radiation oncology, biology, physics.

[10]  M. Mohty,et al.  Prognostic impact of 18F-fluoro-deoxyglucose positron emission tomography in untreated mantle cell lymphoma: a retrospective study from the GOELAMS group , 2010, European Journal of Nuclear Medicine and Molecular Imaging.

[11]  S. Rodenhuis,et al.  The Relevance of Breast Cancer Subtypes in the Outcome of Neoadjuvant Chemotherapy , 2010, Annals of Surgical Oncology.

[12]  Marc Espié,et al.  Early monitoring of response to neoadjuvant chemotherapy in breast cancer with 18F-FDG PET/CT: defining a clinical aim , 2011, European Journal of Nuclear Medicine and Molecular Imaging.

[13]  D. Groheux,et al.  Correlation of high 18F-FDG uptake to clinical, pathological and biological prognostic factors in breast cancer , 2011, European Journal of Nuclear Medicine and Molecular Imaging.

[14]  R. Jeraj,et al.  Variability of textural features in FDG PET images due to different acquisition modes and reconstruction parameters , 2010, Acta oncologica.

[15]  M. Hatt,et al.  Intratumor Heterogeneity Characterized by Textural Features on Baseline 18F-FDG PET Images Predicts Response to Concomitant Radiochemotherapy in Esophageal Cancer , 2011, The Journal of Nuclear Medicine.

[16]  Drew A. Torigian,et al.  Evolving role of molecular imaging with PET in detecting and characterizing heterogeneity of cancer tissue at the primary and metastatic sites, a plausible explanation for failed attempts to cure malignant disorders , 2011, European Journal of Nuclear Medicine and Molecular Imaging.

[17]  Ronald Boellaard,et al.  Evaluation of a cumulative SUV-volume histogram method for parameterizing heterogeneous intratumoural FDG uptake in non-small cell lung cancer PET studies , 2011, European Journal of Nuclear Medicine and Molecular Imaging.

[18]  M. Hatt,et al.  Reproducibility of Tumor Uptake Heterogeneity Characterization Through Textural Feature Analysis in 18F-FDG PET , 2012, The Journal of Nuclear Medicine.

[19]  D. Groheux,et al.  Prognostic Impact of 18FDG-PET-CT Findings in Clinical Stage III and IIB Breast Cancer , 2012, Journal of the National Cancer Institute.

[20]  Patrick Granton,et al.  Radiomics: extracting more information from medical images using advanced feature analysis. , 2012, European journal of cancer.

[21]  S. Rodenhuis,et al.  Association of primary tumour FDG uptake with clinical, histopathological and molecular characteristics in breast cancer patients scheduled for neoadjuvant chemotherapy , 2012, European Journal of Nuclear Medicine and Molecular Imaging.

[22]  D. Narayanan,et al.  Breast cancer detection using high-resolution breast PET compared to whole-body PET or PET/CT , 2014, European Journal of Nuclear Medicine and Molecular Imaging.

[23]  M. Hatt,et al.  Comparison Between 18F-FDG PET Image–Derived Indices for Early Prediction of Response to Neoadjuvant Chemotherapy in Breast Cancer , 2013, The Journal of Nuclear Medicine.

[24]  Vicky Goh,et al.  Are Pretreatment 18F-FDG PET Tumor Textural Features in Non–Small Cell Lung Cancer Associated with Response and Survival After Chemoradiotherapy? , 2013, The Journal of Nuclear Medicine.

[25]  C. Coutant,et al.  Prognostic relevance at 5 years of the early monitoring of neoadjuvant chemotherapy using 18F-FDG PET in luminal HER2-negative breast cancer , 2014, European Journal of Nuclear Medicine and Molecular Imaging.

[26]  H. Linden,et al.  Novel methods and tracers for breast cancer imaging. , 2013, Seminars in nuclear medicine.

[27]  C. Coutant,et al.  18F-FDG PET/CT provides powerful prognostic stratification in the primary staging of large breast cancer when compared with conventional explorations , 2014, European Journal of Nuclear Medicine and Molecular Imaging.

[28]  S. Glück,et al.  Pathologic complete response predicts recurrence-free survival more effectively by cancer subset: Results from the I-SPY 1 TRIAL-CALGB 150007/150012, ACRIN 6657 , 2013 .

[29]  M. Hatt,et al.  Robustness of intratumour 18F-FDG PET uptake heterogeneity quantification for therapy response prediction in oesophageal carcinoma , 2013, European Journal of Nuclear Medicine and Molecular Imaging.

[30]  A. Alavi,et al.  Oncogene pathway activation in mammary tumors dictates FDG-PET uptake. , 2014, Cancer research.

[31]  P. Lambin,et al.  Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach , 2014, Nature Communications.

[32]  S. Son,et al.  Prognostic implication of intratumoral metabolic heterogeneity in invasive ductal carcinoma of the breast , 2014, BMC Cancer.

[33]  Vicky Goh,et al.  Correlation of Intra-Tumor 18F-FDG Uptake Heterogeneity Indices with Perfusion CT Derived Parameters in Colorectal Cancer , 2014, PloS one.

[34]  Ross Berbeco,et al.  Comparison of Texture Features Derived from Static and Respiratory-Gated PET Images in Non-Small Cell Lung Cancer , 2014, PloS one.

[35]  F. Brooks,et al.  The Effect of Small Tumor Volumes on Studies of Intratumoral Heterogeneity of Tracer Uptake , 2014, The Journal of Nuclear Medicine.

[36]  I. Apostolova,et al.  Asphericity of pretherapeutic tumour FDG uptake provides independent prognostic value in head-and-neck cancer , 2014, European Radiology.

[37]  Sung-Bae Kim,et al.  Lapatinib with trastuzumab for HER2-positive early breast cancer (NeoALTTO): survival outcomes of a randomised, open-label, multicentre, phase 3 trial and their association with pathological complete response. , 2014, The Lancet. Oncology.

[38]  Evaluating heterogeneity of primary tumor 18F-FDG uptake in breast cancer with a dedicated breast PET (MAMMI): a feasibility study based on correlation with PET/CT , 2014, Nuclear medicine communications.

[39]  Florent Tixier,et al.  Visual Versus Quantitative Assessment of Intratumor 18F-FDG PET Uptake Heterogeneity: Prognostic Value in Non–Small Cell Lung Cancer , 2014, The Journal of Nuclear Medicine.

[40]  M. Soussan,et al.  Relationship between Tumor Heterogeneity Measured on FDG-PET/CT and Pathological Prognostic Factors in Invasive Breast Cancer , 2014, PloS one.

[41]  D. Groheux,et al.  Prognostic impact of 18F-FDG PET/CT staging and of pathological response to neoadjuvant chemotherapy in triple-negative breast cancer , 2015, European Journal of Nuclear Medicine and Molecular Imaging.

[42]  M. Hatt,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 , 2015, The Journal of Nuclear Medicine.