Dataset Information

Predictive Value of FDG PET/CT to Detect Lymph Node Metastases in Cervical Cancer.

ABSTRACT: PURPOSE:The aim of this study was to determine the prognostic significance of PET/CT findings in women with cervical cancer and describe the normalization of lymph node SUVmax (nSUVmax). MATERIALS AND METHODS:A retrospective review was performed of 113 patients with cervical cancer who underwent a PET/CT before receiving definitive therapy. SUVmax measurements were normalized to the SUV of the pelvic blood pool. Patient, tumor, and PET/CT data were correlated to extracervical recurrence-free survival (ecRFS) and lymph node pathology. RESULTS:Of 113 patients, there were 23 (20%) extracervical recurrences. On univariate analysis, stage, histology, nSUVmax, and radiographic size of the primary tumor, and nSUVmax of the most hypermetabolic lymph node were significantly associated with ecRFS. On multivariable analysis, nSUVmax and radiographic size of the primary tumor remained associated with ecRFS (both P < 0.001). Sixty-six patients underwent pelvic, common iliac, and/or para-aortic nodal sampling. The sensitivity, specificity, false-negative, and false-positive rates of PET/CT for lymph node metastases were 53%, 75%, 6%, and 82%, respectively. On univariate analysis, nSUVmax, and radiographic size of the primary tumor, and nSUVmax of the most hypermetabolic lymph node, and radiographic size of the largest lymph node, were associated with the presence of at least one pathologically positive lymph node. On multivariable analysis, only the radiographic size of the largest lymph node remained significantly associated with lymph node metastases (P < 0.001). CONCLUSIONS:The size and nSUVmax of the primary tumor were associated with ecRFS. PET/CT has a low false-negative rate but high false-positive rate for lymph node metastases.

SUBMITTER: Brunette LL

PROVIDER: S-EPMC7456572 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Predictive Value of FDG PET/CT to Detect Lymph Node Metastases in Cervical Cancer.

Brunette Laurie L LL Bonyadlou Shahram S Ji Lingyun L Groshen Susan S Shuster Dena D Mehta Arjun A Sposto Richard R Matsuo Koji K Lin Yvonne G YG Roman Lynda D LD

Clinical nuclear medicine 20181101 11

<h4>Purpose</h4>The aim of this study was to determine the prognostic significance of PET/CT findings in women with cervical cancer and describe the normalization of lymph node SUVmax (nSUVmax).<h4>Materials and methods</h4>A retrospective review was performed of 113 patients with cervical cancer who underwent a PET/CT before receiving definitive therapy. SUVmax measurements were normalized to the SUV of the pelvic blood pool. Patient, tumor, and PET/CT data were correlated to extracervical recu ...[more]

PMID: 30153151

Similar Datasets

Project description:ObjectivesThe accurate assessment of lymph node metastases (LNMs) and the preoperative nodal (N) stage are critical for the precise treatment of patients with gastric cancer (GC). The diagnostic performance, however, of current imaging procedures used for this assessment is sub-optimal. Our aim was to investigate the value of preoperative 18F-FDG PET/CT radiomic features to predict LNMs and the N stage.MethodsWe retrospectively collected clinical and 18F-FDG PET/CT imaging data of 185 patients with GC who underwent total or partial radical gastrectomy. Patients were allocated to training and validation sets using the stratified method at a fixed ratio (8:2). There were 2,100 radiomic features extracted from the 18F-FDG PET/CT scans. After selecting radiomic features by the random forest, relevancy-based, and sequential forward selection methods, the BalancedBagging ensemble classifier was established for the preoperative prediction of LNMs, and the OneVsRest classifier for the N stage. The performance of the models was primarily evaluated by the AUC and accuracy, and validated by the independent validation methods. Analysis of the feature importance and the correlation were also conducted. We also compared the predictive performance of our radiomic models to that with the contrast-enhanced CT (CECT) and 18F-FDG PET/CT.ResultsThere were 185 patients-127 men, 58 women, with the median age of 62, and an age range of 22-86 years. One CT feature and one PET feature were selected to predict LNMs and achieved the best performance (AUC: 82.2%, accuracy: 85.2%). This radiomic model also detected some LNMs that were missed in CECT (19.6%) and 18F-FDG PET/CT (35.7%). For predicting the N stage, four CT features and one PET feature were selected (AUC: 73.7%, accuracy: 62.3%). Of note, a proportion of patients in the validation set whose LNMs were incorrectly staged by CECT (57.4%) and 18F-FDG PET/CT (55%) were diagnosed correctly by our radiomic model.ConclusionWe developed and validated two machine learning models based on the preoperative 18F-FDG PET/CT images that have a predictive value for LNMs and the N stage in GC. These predictive models show a promise to offer a potentially useful adjunct to current staging approaches for patients with GC.

Project description:ObjectivesTo compare the diagnostic accuracy of preoperative 18F-FDG PET/CT and MRI tumor markers for prediction of lymph node metastases (LNM) and aggressive disease in endometrial cancer (EC).MethodsPreoperative whole-body 18F-FDG PET/CT and pelvic MRI were performed in 215 consecutive patients with histologically confirmed EC. PET/CT-based tumor standardized uptake value (SUVmax and SUVmean), metabolic tumor volume (MTV), and PET-positive lymph nodes (LNs) (SUVmax >?2.5) were analyzed together with the MRI-based tumor volume (VMRI), mean apparent diffusion coefficient (ADCmean), and MRI-positive LN (maximum short-axis diameter ??10 mm). Imaging parameters were explored in relation to surgicopathological stage and tumor grade. Receiver operating characteristic (ROC) curves were generated yielding optimal cutoff values for imaging parameters, and regression analyses were used to assess their diagnostic performance for prediction of LNM and progression-free survival.ResultsFor prediction of LNM, MTV yielded the largest area under the ROC curve (AUC) (AUC?=?0.80), whereas VMRI had lower AUC (AUC?=?0.72) (p?=?0.03). Furthermore, MTV >?27 ml yielded significantly higher specificity (74%, p?<?0.001) and accuracy (75%, p?<?0.001) and also higher odds ratio (12.2) for predicting LNM, compared with VMRI >?10 ml (58%, 62%, and 9.7, respectively). MTV >?27 ml also tended to yield higher sensitivity than PET-positive LN (81% vs 50%, p?=?0.13). Both VMRI >?10 ml and MTV >?27 ml were significantly associated with reduced progression-free survival.ConclusionsTumor markers from 18F-FDG PET/CT outperform MRI markers for the prediction of LNM. MTV >?27 ml yields a high diagnostic performance for predicting aggressive disease and represents a promising supplement to conventional PET/CT reading in EC.Key points• Metabolic tumor volume (MTV) outperforms other 18F-FDG PET/CT and MRI markers for preoperative prediction of lymph node metastases (LNM) in endometrial cancer patients. • Using cutoff values for tumor volume for prediction of LNM, MTV >?27 ml yielded higher specificity and accuracy than VMRI>?10 ml. • MTV represents a promising supplement to conventional PET/CT reading for predicting aggressive disease in EC.

Project description:Positron lymphography using 18F-FDG followed by Cerenkov-guided resection of lymph nodes in healthy mice has previously been introduced by our group. Our aim in this study was to further assess the technique's potential beyond merely localizing sentinel lymph nodes. We now aimed to evaluate the potential of positron lymphography to characterize the nodes with respect to their tumor status in order to identify metastatic lymph nodes. We explored whether metastatic nodes could be distinguished from normal nodes via dynamic 18F-FDG lymphography, to then be resected under Cerenkov imaging guidance. Methods: A murine melanoma cell line highly metastatic to lymph nodes (B16F10) was implanted subcutaneously on the dorsal hind paw of C57 mice while the tumor-free contralateral leg served as an intraindividual control. A model of reactive lymph nodes after concanavalin A challenge served as an additional control to provide nonmalignant inflammatory lymphadenopathy. Dynamic PET/CT imaging was performed immediately after injection of 18F-FDG around the tumor or intracutaneously in the contralateral footpad. Furthermore, PET/CT and Cerenkov studies were performed repeatedly over time to follow the course of metastatic spread. In selected mice, popliteal lymph nodes underwent Cerenkov luminescence imaging. Hematoxylin and eosin staining was done to verify the presence of lymphatic melanoma infiltration. Results: Positron lymphography using 18F-FDG was successfully performed on tumor-bearing and non-tumor-bearing mice, as well as on controls bearing sites of inflammation; the results clearly identified the sentinel lymph node basin and delineated the lymphatic drainage. Significantly prolonged retention of activity was evident in metastatic nodes as compared with controls without tumor. On the basis of these results, the contrast in detection and identification of metastatic lymph nodes was distinct and could be used for guided lymph node resection, such as by using Cerenkov luminescence imaging. However, retention after 18F-FDG lymphography was also seen in acute inflammatory lymphadenopathy. Conclusion: In a tumor model, significantly longer retention of the radiotracer during 18F-FDG lymphography was seen in metastatic than nonmetastatic lymph nodes, allowing for differentiation between the two and for selective resection of tumor-bearing nodes using Cerenkov imaging. Inflammation can be better differentiated in a subacute state.

Dataset Information

Predictive Value of FDG PET/CT to Detect Lymph Node Metastases in Cervical Cancer.

Publications

Predictive Value of FDG PET/CT to Detect Lymph Node Metastases in Cervical Cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets