Relationship between tumor heterogeneity measured on FDG-PET/CT and pathological prognostic factors in invasive breast cancer.
BACKGROUND
There is currently little support to understand which pathological factors led to differences in tumor texture as measured from FDG PET/CT images. We studied whether tumor heterogeneity measured using texture analysis in FDG-PET/CT images is correlated with pathological prognostic factors in invasive breast cancer.


METHODS
Fifty-four patients with locally advanced breast cancer who had an initial FDG-PET/CT were retrospectively included. In addition to SUVmax, three robust textural indices extracted from 3D matrices: High-Gray-level Run Emphasis (HGRE), Entropy and Homogeneity were studied. Univariate and multivariate logistic regression was used to identify PET parameters associated with poor prognosis pathological factors: hormone receptor negativity, presence of HER-2 and triple negative phenotype. Receiver operating characteristic (ROC) curves and the (AUC) analysis, and reclassification measures, were performed in order to evaluate the performance of combining texture analysis and SUVmax for characterizing breast tumors.


RESULTS
Tumor heterogeneity, measured with HGRE, was higher in negative estrogen receptor (p = 0.039) and negative progesterone receptor tumors (p = 0.036), and in Scarff-Bloom-Richardson grade 3 tumors (p = 0.047). None of the PET indices could identify HER-2 positive tumors. Only SUVmax was positively correlated with Ki-67 (p<0.0004). Triple negative breast cancer (TNBC) exhibited higher SUVmax (Odd Ratio = 1.22, 95%CI [1.06-1.39],p = 0.004), lower Homogeneity (OR = 3.57[0.98-12.5],p = 0.05) and higher HGRE (OR = 8.06[1.88-34.51],p = 0.005) than non-TNBC. Multivariate analysis showed that HGRE remained associated with TNBC (OR = 5.27[1.12-1.38],p = 0.03) after adjustment for SUVmax. Combining SUVmax and HGRE yielded in higher area under the ROC curves (AUC) than SUVmax for identifying TNBC: AUC =  0.83 and 0.77, respectively. Probability of correct classification also increased in 77% (10/13) of TNBC and 71% (29/41) of non-TNBC (p = 0.003), when combining SUVmax and HGRE.


CONCLUSIONS
Tumor heterogeneity measured on FDG-PET/CT was higher in invasive breast cancer with poor prognosis pathological factors. Texture analysis might be used, in addition to SUVmax, as a new tool to assess invasive breast cancer aggressiveness.
Paris 13 University, Sorbonne Paris Cité, Bobigny, France; Department of Nuclear Medicine, AP-HP, Avicenne University Hospital, Bobigny, France; IMNC - UMR 8165 CNRS - Paris 7 and Paris 11 Universities, Orsay, France.
Michael
M
Soussan
IMNC - UMR 8165 CNRS - Paris 7 and Paris 11 Universities, Orsay, France.
Fanny
F
Orlhac
Clinical Research Unit, AP-HP, Avicenne University Hospital, Bobigny, France.
Marouane
M
Boubaya
Paris 13 University, Sorbonne Paris Cité, Bobigny, France; Department of Oncology, AP-HP, Avicenne University Hospital, Bobigny, France.
Laurent
L
Zelek
Paris 13 University, Sorbonne Paris Cité, Bobigny, France; Department of Pathology, AP-HP, Jean Verdier Hospital, Bondy, France.
Marianne
M
Ziol
Paris 13 University, Sorbonne Paris Cité, Bobigny, France; Department of Nuclear Medicine, AP-HP, Avicenne University Hospital, Bobigny, France.
Véronique
V
Eder
CEA-SHFJ, Orsay, France.
Irène
I
Buvat
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D019540:Area Under Curve; D001943:Breast Neoplasms / Q000000981:diagnostic imaging*; D005260:Female; D019788:Fluorodeoxyglucose F18; D006801:Humans; D021621:Imaging, Three-Dimensional; D007150:Immunohistochemistry; D008875:Middle Aged; D064847:Multimodal Imaging; D015999:Multivariate Analysis; D009361:Neoplasm Invasiveness; D049268:Positron-Emission Tomography / Q000379:methods*; D011379:Prognosis; D012372:ROC Curve; D019275:Radiopharmaceuticals; D014057:Tomography, X-Ray Computed / Q000379:methods*; D064726:Triple Negative Breast Neoplasms / Q000000981:diagnostic imaging
D019275:Radiopharmaceuticals; D019788:Fluorodeoxyglucose F18