Metabolic parameters using 18F-FDG PET/CT correlate with occult lymph node metastasis in squamous cell lung carcinoma

Zhang²,

et al. 2020

J. Cancer

Background: It has been rarely reported whether 18 F-fluorodeoxyglucose (18 F-FDG) uptake in colorectal cancer cells is associated with the expression of PD-L1. We performed a clinical pathology study to evaluate PD-L1 expression in patients undergoing surgical resection of colorectal cancer with preoperative 18 F-FDG PET/CT imaging, with the aim of predicting the response of CRC patients to immune checkpoint inhibitors. Material and Methods: A retrospective analysis of patients with CRC who underwent FDG-PET imaging before surgery was performed to measure the parameters of FDG-PET imaging: the maximum standardized uptake value (SUVmax), the metabolic tumor volume (MTV), and the total lesion glycolysis (TLG) were evaluated to determine whether each parameter was associated with clinical pathology. Tumor specimens were subjected to PD-L1 staining by immunohistochemistry. Analysis of whether there is a correlation between PD-L1 expression and 18 F-FDG uptake parameters in CRC. Results: PD-L1 expression level was significantly correlated with SUVmax, MTV3.0 and TLG3.0. Multivariate analysis showed that PD-L1 and TLG3.0 were independent predictors of poor DFS in patients with CRC (P=0.009; P=0.016), PD-L1 expression is closely related to the patient's lesion (TLG3.0) (P＜0.01). Conclusion: The results of this study indicate that there was a significant correlation between PD-L1 expression and TLG3.0 which suggested that FDG-PET could serve as a noninvasive tool to assess the tumor microenvironment and as a predictor of PD-L1 inhibitor activity to determine the optimal therapeutic strategy for CRC. High PD-L1 expression levels and high TLG3.0 are independent risk factors for DFS differences in CRC patients.

Section: Ivyspringmentioning

confidence: 99%

Retrospective analysis of the prognostic value of PD-L1 expression and ¹⁸F-FDG PET/CT metabolic parameters in colorectal cancer

Zhang²,

et al. 2020

J. Cancer

“…[6][7][8][9] Several studies have shown that metabolic activity of primary tumor on 18 F-FDG PET/CT can predict lymph node (LN) metastasis in various cancers. [10][11][12][13][14][15] However, breast cancer is a remarkably heterogeneous disease consisting of biologically distinct tumor subtypes. Many previous studies have shown a good correlation between 18 F-FDG uptake by primary tumor and molecular subtypes of breast cancer.…”

mentioning

confidence: 99%

Predictive Value of 18F-FDG PET/CT for Axillary Lymph Node Metastasis in Invasive Ductal Breast Cancer

2017

Self Cite

“…In a multivariate analysis SUV max was independent of tumour size and importantly type of tumour, for predicting the presence of occult lymph node metastasis . In an initial study of 63 patients, an Optimal cut‐off value of 8.8 SUV max of the primary tumour was shown to predict occult metastases in NSCLC although in another larger cohort ( n = 163), an SUV max of 7 was deemed to be the best threshold for indicating metastatic risk; a value <7 was shown to be an independent prognostic factor for metastasis‐free survival . High SUV as an independent biomarker of prognosis has been borne out in lung cancer (meta‐analysis of 21 lung cancer studies had a combined hazard ratio of 2.08), in breast cancer (hazard ratio 2.39) and in soft‐tissue sarcoma (hazard ratio 3.75), where it has been related to mitotic count .…”

Section: Metastatic Risk Assessmentmentioning

confidence: 99%

“…Angiogenic features, maximum standardised uptake value on FDG-PET, apparent diffusion coefficient on MRI are all linked to tumour grade and metastatic risk, [25][26][27][28][29][30][31][32][33][34][35][36][37][38][39] but no evidence for their use in distinguishing OM from PM…”

Section: Functional Imaging Featuresmentioning

confidence: 99%

A risk‐based approach to identifying oligometastatic disease on imaging

deSouza

Tempany

2018

Intl Journal of Cancer

Recognition of <3 metastases in <2 organs, particularly in cancers with a known predisposition to oligometastatic disease (OMD) (colorectal, prostate, renal, sarcoma and lung), offers the opportunity to focally treat the lesions identified and confers a survival advantage. The reliability with which OMD is identified depends on the sensitivity of the imaging technique used for detection and may be predicted from phenotypic and genetic factors of the primary tumour, which determine metastatic risk. Whole-body or organ-specific imaging to identify oligometastases requires optimization to achieve maximal sensitivity. Metastatic lesions at multiple locations may require a variety of imaging modalities for best visualisation because the optimal image contrast is determined by tumour biology. Newer imaging techniques used for this purpose require validation. Additionally, rationalisation of imaging strategies is needed, particularly with regard to timing of imaging and follow-up studies. This article reviews the current evidence for the use of imaging for recognising OMD and proposes a risk-based roadmap for identifying patients with true OMD, or at risk of metastatic disease likely to be OM.