Combining positron emission tomography/computed tomography, radiomics, and sentinel lymph node mapping for nodal staging of endometrial cancer patients. Issue 3 (19th February 2020) - Crivellaro, Cinzia; Landoni, Claudio; Elisei, Federica; Buda, Alessandro; Bonacina, Manuela; Grassi, Tommaso; Monaco, Lavinia; Giuliani, Daniela; Gotuzzo, Irene; Magni, Sonia; Di Martino, Giampaolo; Delle Marchette, Martina; et al.
Abstract : Objective: To evaluate the combination of positron emission tomography/computed tomography (PET/CT) and sentinel lymph node (SLN) biopsy in women with apparent early-stage endometrial carcinoma. The correlation between radiomics features extracted from PET images of the primary tumor and the presence of nodal metastases was also analyzed. Methods: From November 2006 to March 2019, 167 patients with endometrial cancer were included. All women underwent PET/CT and surgical staging: 60/167 underwent systematic lymphadenectomy (Group 1) while, more recently, 107/167 underwent SLN biopsy (Group 2) with technetium-99m +blue dye or indocyanine green. Histology was used as standard reference. PET endometrial lesions were segmented (n=98); 167 radiomics features were computed inside tumor contours using standard Image Biomarker Standardization Initiative (IBSI) methods. Radiomics features associated with lymph node metastases were identified (Mann-Whitney test) in the training group (A); receiver operating characteristic (ROC) curves, area under the curve (AUC) values were computed and optimal cut-off (Youden index) were assessed in the test group (B). Results: In Group 1, eight patients had nodal metastases (13%): seven correctly ridentified by PET/CT true-positive with one false-negative case. In Group 2, 27 patients (25%) had nodal metastases: 13 true-positive and 14 false-negative. Sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of PET/CT for pelvic nodal metastases were 87%, 94%, 93%, 70%, and 98% in Group 1 and 48%, 97%, 85%, 87%, and 85% in Group 2, respectively. On radiomics analysis a significant association was found between the presence of lymph node metastases and 64 features. Volume-density, a measurement of shape irregularity, was the most predictive feature (p=0001, AUC=0, 77, cut-off 0.35). When t esting cut-off in Group B to discriminate metastatic tumors, PET false-negative findings were reduced from 14 to 8 (-43%). Conclusions: PET/CT demonstrated high specificity in detecting nodal metastases. SLN and histologic ultrastaging increased false-negative PET/CT findings, reducing the sensitivity of the technique. PET radiomics features of the primary tumor seem promising for predicting the presence of nodal metastases not detected by visual analysis.