Dataset Information

Preoperative Nodal ¹⁸F-FDG Avidity Rather than Primary Tumor Avidity Determines the Prognosis of Patients with Advanced Gastric Cancer.

ABSTRACT:

Purpose

This study investigated whether the metabolic avidity of primary tumors and/or metastatic lymph nodes (LNs) measured by ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography/computed tomography (PET/CT) was related to survival after surgery in patients with advanced gastric cancer (AGC).

Materials and methods

One hundred sixty-eight patients with AGC who underwent preoperative ¹⁸F-FDG PET/CT and curative resection were included. The ¹⁸F-FDG avidity of the primary gastric tumor and LNs was determined quantitatively and qualitatively. The diagnostic performance of ¹⁸F-FDG PET/CT was calculated, and the prognostic significance of ¹⁸F-FDG avidity for recurrence-free survival (RFS) and overall survival (OS) was assessed.

Results

In all, 51 (30.4%) patients experienced recurrence, and 32 (19.0%) died during follow-up (median follow-up duration, 35 months; range, 3-81 months); 119 (70.8%) and 33 (19.6%) patients showed ¹⁸F-FDG-avid primary tumors and LNs, respectively. ¹⁸F-FDG PET/CT showed high sensitivity (73.8%) for the detection of advanced pathologic T (pT ?3) stage and high specificity (92.2%) for the detection of advanced pN (?2) stage. ¹⁸F-FDG avidity of LNs was significantly associated with RFS (P=0.012), whereas that of primary tumors did not show significance (P=0.532). Univariate and multivariate analyses revealed that ¹⁸F-FDG avidity of LNs was an independent prognostic factor for RFS (hazard ratio=2.068; P=0.029).

Conclusions

¹⁸F-FDG avidity of LNs is an independent prognostic factor for predicting RFS. Preoperative ¹⁸F-FDG PET/CT can be used to determine the risk and prognosis of patients with AGC after curative resection.

SUBMITTER: Kwon HW

PROVIDER: S-EPMC6160526 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Publications

Preoperative Nodal <sup>18</sup>F-FDG Avidity Rather than Primary Tumor Avidity Determines the Prognosis of Patients with Advanced Gastric Cancer.

Kwon Hyun Woo HW An Liang L Kwon Hye Ryeong HR Park Sungsoo S Kim Sungeun S

Journal of gastric cancer 20180810 3

<h4>Purpose</h4>This study investigated whether the metabolic avidity of primary tumors and/or metastatic lymph nodes (LNs) measured by <sup>18</sup>F-fluorodeoxyglucose (<sup>18</sup>F-FDG) positron emission tomography/computed tomography (PET/CT) was related to survival after surgery in patients with advanced gastric cancer (AGC).<h4>Materials and methods</h4>One hundred sixty-eight patients with AGC who underwent preoperative <sup>18</sup>F-FDG PET/CT and curative resection were included. The ...[more]

PMID: 30275999

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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:BackgroundSurgical resection remains the mainstay of curative treatment for intrahepatic cholangiocarcinoma (ICC). Prognosis after surgery is unsatisfactory despite improvements in treatment and post-operative clinical management. Despite developments in the molecular profiling of ICC, the preoperative prediction of prognosis remains a challenge. This study aimed to identify clinical prognostic indicators by investigating the molecular profiles of ICC and evaluating the preoperative imaging data of 18F-fluorodeoxyglucose positron emission tomography (18F-FDG-PET).MethodsA retrospective analysis was performed on 50 consecutive patients with ICC who underwent curative hepatectomy after 18F-FDG-PET examination. To evaluate the molecular profiles of ICC, KRAS mutation status was assessed in resected specimens. For the assessment of glucose uptake, we observed the expression of glucose transporter-1 (GLUT-1) by immunohistochemistry. The data of 18F-FDG-PET were re-evaluated as follows: maximum standardized uptake value, metabolic tumor volume (MTV), and total lesion glycolysis (TLG). Cut-off values were determined using receiver operating characteristic (ROC) curve analysis. Cumulative overall survival (OS) was analyzed using the Kaplan-Meier analysis.ResultsOverall, 16 (32.0%) patients had mutations in KRAS. Patients with mutated KRAS exhibited shorter OS than those with wild-type KRAS (5-year OS, 0% vs. 35.1%, P?<?0.001). GLUT-1 expression was significantly higher in tumors with mutated KRAS than in tumors with wild-type KRAS (median, 4.0 vs. 1.0, P?<?0.001). Survival was significantly different when stratified by expression of GLUT-1 (5-year OS, 0% vs. 46.5%, P?<0.001). Among the 18F-FDG-PET parameters, the MTV and TLG were significantly higher in the mutated KRAS group than in the wild-type KRAS group (P?=?0.013 and P?=?0.026, respectively). ROC curve analysis revealed a cut-off value of 38 for the MTV, with the highest accuracy (area under the curve?=?0.789; 95% confidence interval, 0.581-0.902) for predicting KRAS mutation. This cut-off value permitted stratification of OS (high vs. low: 5-year OS, 13.1% vs. 36.7%, P?=?0.008).ConclusionsHigh MTV is associated with KRAS mutation and poor postoperative outcomes in patients with ICC, suggesting that the MTV of ICC measured by 18F-FDG-PET may provide useful information for tumor molecular profiles and prognosis.

Dataset Information

Preoperative Nodal ¹⁸F-FDG Avidity Rather than Primary Tumor Avidity Determines the Prognosis of Patients with Advanced Gastric Cancer.

Purpose

Materials and methods

Results

Conclusions

Publications

Preoperative Nodal <sup>18</sup>F-FDG Avidity Rather than Primary Tumor Avidity Determines the Prognosis of Patients with Advanced Gastric Cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset Information

Preoperative Nodal 18F-FDG Avidity Rather than Primary Tumor Avidity Determines the Prognosis of Patients with Advanced Gastric Cancer.

Purpose

Materials and methods

Results

Conclusions

Publications

Preoperative Nodal <sup>18</sup>F-FDG Avidity Rather than Primary Tumor Avidity Determines the Prognosis of Patients with Advanced Gastric Cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Preoperative Nodal ¹⁸F-FDG Avidity Rather than Primary Tumor Avidity Determines the Prognosis of Patients with Advanced Gastric Cancer.