Evaluation of lymph node metastases in gastric cancer with spiral computed tomography

Background—Much controversy exists as to the value of computed tomography (CT) in the preoperative staging of gastric cancer, because of its limited ability to identify correctly lymph node (LN) metastases, invasion of adjacent organs, or hepatic and peritoneal metastases. Spiral CT scanners have a number of potential advantages over conventional scanners, including the absence of respiratory misregistration, image reconstruction smaller than scan collimation permitting overlapping slices and optimisation of intravenous contrast enhancement.Aim—To compare the performance of spiral CT and operative assessment against formal (TNM) pathological staging.Patients and methods—A study of 105 consecutive patients who underwent both spiral CT and operative staging was performed. All CT scans were reviewed by a radiologist who commented on tumour location and size, evidence of adjacent organ invasion, lymph node metastases to both N1 and N2 nodes, and evidence of hepatic and peritoneal metastases. All patients underwent careful operative assessment at the time of surgery, along the lines suggested by Rohde and colleagues.Results—Spiral CT remained poor at identifying LN metastases to both N1 and N2 lymph nodes, with sensitivity ranging from 24 to 43%; specificity, however, was 100%. Operative staging was superior, with sensitivities between 84 and 94%, but specificity was much lower (63–74%). Spiral CT correctly detected 13 of 17 cases of invasion of either the colon or the mesocolon (sensitivity 76%) compared with 16 of 17 cases at operative staging (sensitivity 94%). Spiral CT correctly identified three of six cases with invasion of the pancreas (sensitivity 50%) compared with six of six cases on operative staging (sensitivity 100%). Spiral CT correctly identified 12 of 17 cases of peritoneal metastases (sensitivity 71%) and four of seven cases of hepatic metastases (sensitivity 57%).Conclusion—Whilst spiral CT remains poor at identifying lymph node metastases, it correctly identified most cases with invasion of either the colon or the mesocolon and half the cases of pancreatic invasion. It was of value in detecting peritoneal metastases and some cases with hepatic metastases. At present, at Leeds General Infirmary spiral CT is performed routinely on all patients with gastric cancer and a selective staging laparoscopy policy is adopted in those patients in whom the status of the peritoneal cavity and liver is in doubt.

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Prediction of Lymph Node Metastases in Gastric Cancer by Serum APE1 Expression

Journal of Cancer ◽

10.7150/jca.18615 ◽

2017 ◽

Vol 8 (8) ◽

pp. 1492-1497 ◽

Cited By ~ 12

Author(s):

Xi Wei ◽

Yi-bo Li ◽

Ying Li ◽

Ben-cheng Lin ◽

Xiao-Min Shen ◽

...

Keyword(s):

Gastric Cancer ◽

Lymph Node ◽

Lymph Node Metastases ◽

Node Metastases

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Assessment of cervical lymph node metastases using indirect computed tomography lymphography with iopamidol in a tongue VX2 carcinoma model

The Journal of Laryngology & Otology ◽

10.1017/s0022215111000958 ◽

2011 ◽

Vol 125 (8) ◽

pp. 820-828 ◽

Cited By ~ 4

Author(s):

Y Shu ◽

X Xu ◽

Z Wang ◽

W Dai ◽

Y Zhang ◽

...

Keyword(s):

Computed Tomography ◽

Lymph Node ◽

Lymph Nodes ◽

Lymph Node Metastases ◽

Cervical Lymph Node ◽

Cervical Lymph Nodes ◽

Cervical Lymph Node Metastases ◽

Computed Tomography Images ◽

Vx2 Carcinoma ◽

Node Metastases

AbstractObjective:To investigate the performance of indirect computed tomography lymphography with iopamidol for detecting cervical lymph node metastases in a tongue VX2 carcinoma model.Materials and methods:A metastatic cervical lymph node model was created by implanting VX2 carcinoma suspension into the tongue submucosa of 21 rabbits. Computed tomography images were obtained 1, 3, 5, 10, 15 and 20 minutes after iopamidol injection, on days 11, 14, 21 (six rabbits each) and 28 (three rabbits) after carcinoma transplantation. Computed tomography lymphography was performed, and lymph node filling defects and enhancement characteristics evaluated.Results:Indirect computed tomography lymphography revealed bilateral enhancement of cervical lymph nodes in all animals, except for one animal imaged on day 28. There was significantly slower evacuation of contrast in metastatic than non-metastatic nodes. A total of 41 enhanced lymph nodes displayed an oval or round shape, or local filling defects. One lymph node with an oval shape was metastatic (one of 11, 9.1 per cent), while 21 nodes with filling defects were metastatic (21/30, 70 per cent). The sensitivity, specificity, accuracy, and positive and negative predictive values when using a filling defect diameter of 1.5 mm as a diagnostic criterion were 86.4, 78.9, 82.9, 82.6 and 83.3 per cent, respectively.Conclusion:When using indirect computed tomography lymphography to detect metastatic lymph nodes, filling defects and slow evacuation of contrast agent are important diagnostic features.

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The superiority of 256-slice spiral computed tomography angiography for preoperative evaluation of surrounding arteries in patients with gastric cancer

OncoTargets and Therapy ◽

10.2147/ott.s88330 ◽

2017 ◽

Vol Volume 10 ◽

pp. 927-933 ◽

Cited By ~ 2

Author(s):

Deqing Wu ◽

Linyong Zhao ◽

Ying Liu ◽

Junjiang Wang ◽

Weixian Hu ◽

...

Keyword(s):

Gastric Cancer ◽

Computed Tomography ◽

Computed Tomography Angiography ◽

Preoperative Evaluation ◽

Spiral Computed Tomography ◽

Spiral Computed

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18F-FDG PET/CT Radiomics for Preoperative Prediction of Lymph Node Metastases and Nodal Staging in Gastric Cancer

Frontiers in Oncology ◽

10.3389/fonc.2021.723345 ◽

2021 ◽

Vol 11 ◽

Author(s):

Qiufang Liu ◽

Jiaru Li ◽

Bowen Xin ◽

Yuyun Sun ◽

Dagan Feng ◽

...

Keyword(s):

Gastric Cancer ◽

Lymph Node ◽

Lymph Node Metastases ◽

Fdg Pet ◽

Fixed Ratio ◽

Preoperative Prediction ◽

Pet Ct ◽

N Stage ◽

Node Metastases ◽

Fdg Pet Ct

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.

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