Prospective Evaluation of Changes in Tumor Size and Tumor Metabolism in Patients with Advanced Gastric Cancer Undergoing Chemotherapy: Association and Clinical Implication

Prediction model of liver metastasis risk in patients with gastric cancer: A population-based study

Liver was the most common site of distant metastasis in patients with gastric cancer (GC). The prediction model of the risk of liver metastasis was rarely proposed. Therefore, we aimed to establish a prediction model for liver metastasis in patients with GC. In this retrospective cohort study, we extracted demographic and clinical data of all the GC patients from the Surveillance, Epidemiology, and End Results registration database from 2010 to 2015. Patients were divided into training set (n = 1691) for model development and testing set (n = 3943) for validation. Univariable and multivariable logistic regression analyses were carried out on the training set to screen potential predictors of liver metastasis and constructed a prediction model. The receiver operator characteristics curves with the area under curve values were used to assess the predictive performance of the liver metastasis prediction model. And a nomogram of the prediction model was also constructed. Of the total 5634 GC patients, 444 (7.88%) had liver metastasis. Variables including age, gender, N stage, T stage, Lauren classification, tumor size, histological type, and surgery were included in the liver metastasis prediction model. The study results indicated that the model had excellent discriminative ability with an area under curve of 0.851 (95% confidence interval: 0.829-0.873) in the training set, and that of 0.849 (95% confidence interval: 0.813-0.885) in the testing set. We have developed an effective prediction model with 8 easily acquired predictors of liver metastasis. The prediction model could predict the risk of liver metastasis in GC patients and performed well, which would assist clinicians to make individualized prediction of liver metastasis in GC patients and adjust treatment strategies in time to improve the prognosis.

Simplified and highly-reliable automated production of [18F]FSPG for clinical studies

BACKGROUND

(S)-4-(3-¹⁸F-Fluoropropyl)-L-Glutamic Acid ([¹⁸F]FSPG) is a positron emission tomography (PET) tracer that specifically targets the cystine/glutamate antiporter (xc^-), which is frequently overexpressed in cancer and several neurological disorders. Pilot studies examining the dosimetry and biodistribution of [¹⁸F]FSPG in healthy volunteers and tumor detection in patients with non-small cell lung cancer, hepatocellular carcinoma, and brain tumors showed promising results. In particular, low background uptake in the brain, lung, liver, and bowel was observed that further leads to excellent imaging contrasts of [¹⁸F]FSPG PET. However, reliable production-scale cGMP-compliant automated procedures for [¹⁸F]FSPG production are still lacking to further increase the utility and clinical adoption of this radiotracer. Herein, we report the optimized automated approaches to produce [¹⁸F]FSPG through two commercially available radiosynthesizers capable of supporting centralized and large-scale production for clinical use.

RESULTS

Starting with activity levels of 60-85 GBq, the fully-automated process to produce [¹⁸F]FSPG took less than 45 min with average radiochemical yields of 22.56 ± 0.97% and 30.82 ± 1.60% (non-decay corrected) using TRACERlab™ FXFN and FASTlab™, respectively. The radiochemical purities were > 95% and the formulated [¹⁸F]FSPG solution was determined to be sterile and colorless with the pH of 6.5-7.5. No radiolysis of the product was observed up to 8 h after final batch formulation.

CONCLUSIONS

In summary, cGMP-compliant radiosyntheses and quality control of [¹⁸F]FSPG have been established on two commercially available synthesizers leveraging high activity concentration and radiochemical purity. While the clinical trials using [¹⁸F]FSPG PET are currently underway, the automated approaches reported herein will accelerate the clinical adoption of this radiotracer and warrant centralized and large-scale production of [¹⁸F]FSPG.

Imaging glucose metabolism to reveal tumor progression

Purpose: To analyze and review the progress of glucose metabolism-based molecular imaging in detecting tumors to guide clinicians for new management strategies. Summary: When metabolic abnormalities occur, termed the Warburg effect, it simultaneously enables excessive cell proliferation and inhibits cell apoptosis. Molecular imaging technology combines molecular biology and cell probe technology to visualize, characterize, and quantify processes at cellular and subcellular levels in vivo. Modern instruments, including molecular biochemistry, data processing, nanotechnology, and image processing, use molecular probes to perform real-time, non-invasive imaging of molecular and cellular events in living organisms. Conclusion: Molecular imaging is a non-invasive method for live detection, dynamic observation, and quantitative assessment of tumor glucose metabolism. It enables in-depth examination of the connection between the tumor microenvironment and tumor growth, providing a reliable assessment technique for scientific and clinical research. This new technique will facilitate the translation of fundamental research into clinical practice.

18F-5-FPN: A Specific Probe for Monitoring Photothermal Therapy Response in Malignant Melanoma

Previously, we successfully synthesized a ¹⁸F-labeled positron-emission tomography (PET) tracer, termed ¹⁸F-5-fluoro-N-(2-[diethylamino]ethyl)picolinamide (¹⁸F-5-FPN), with high specificity for melanin. In this study, we sought to investigate the value of ¹⁸F-5-FPN in assessing the response to photothermal therapy (PTT) in melanoma via comparison with ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) to reveal an early response, recognize early recurrence, and distinguish the inflammatory response during the treatment. B16F10, inflammatory, and MDA-MB-231 models were subjected to ¹⁸F-FDG PET and ¹⁸F-5-FPN PET static acquisitions. We compared quantitative data to assess the specificity of different agents for different diseases. B16F10 and MDA-MB-231subcutaneous tumor models were irradiated with an 808 nm laser for PTT. Their survival was documented to observe the efficacy of and response to PTT, using ¹⁸F-5-FPN and ¹⁸F-FDG PET. ¹⁸F-5-FPN accumulated in B16F10 cell xenografts only, whereas ¹⁸F-FDG accumulated in all three models. Melanin in B16F10 cell xenografts successfully transformed the optical energy into heat. Hematoxylin and eosin (H&E) staining at 24 h revealed destruction and extensive necrosis of tumor tissue. PTT rapidly inhibited the growth of B16F10 cell xenografts and prolonged the median survival. The mean tumor uptakes of ¹⁸F-5-FPN on day 2 (7.52 ± 3.65 %ID/g) and day 6 (10.22 ± 6.00 %ID/g) were much lower than that before treatment (18.33 ± 4.98 %ID/g, p < 0.01). However, a significant difference in ¹⁸F-FDG uptakes was not found between day 1 after PTT and before treatment. Compared with ¹⁸F-FDG, ¹⁸F-5-FPN PET could estimate PTT efficacy in melanoma, monitor minimal recurrence, and distinguish melanoma from inflammation and other carcinoma types, thanks to its high affinity to melanin. ¹⁸F-5-FPN may provide a new approach for precise and accurate evaluation of response, timely management of therapeutic regimens, and sensitive follow-up.

The role of 18F-FDG PET/CT in patients with diffuse large B-cell lymphoma after radioimmunotherapy using 131I-rituximab as consolidation therapy

Purpose

To evaluate the prognostic value of pretreatment ¹⁸F-FDG PET/CT after consolidation therapy of ¹³¹I-rituximab in patients with diffuse large B-cell lymphoma (DLBCL) who had acquired complete remission after receiving chemotherapy.

Methods

Patients who were diagnosed with DLBCL via histologic confirmation were retrospectively reviewed. All patients had achieved complete remission after 6 to 8 cycles of R-CHOP (rituximab, cyclophosphamide, vincristine, doxorubicin, and prednisolone) chemotherapy after which they underwent consolidation treatment with ¹³¹I-rituximab. ¹⁸F-FDG PET/CT scans were performed before R-CHOP for initial staging. The largest diameter of tumor, maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were obtained from pretreatment ¹⁸F-FDG PET/CT scans. Receiver-operating characteristic curves analysis was introduced for assessing the optimal criteria. Kaplan-Meier curve survival analysis was performed to evaluate both relapse free survival (RFS) and overall survival (OS).

Results

A total of 15 patients (12 males and 3 females) with a mean age of 56 (range, 30–73) years were enrolled. The median follow-up period of these patients was 73 months (range, 11–108 months). Four (27%) patients relapsed. Of them, three died during follow-up. Median values of the largest tumor size, highest SUVmax, MTV, and TLG were 5.3 cm (range, 2.0–16.4 cm), 20.2 (range, 11.1–67.4), 231.51 (range, 15–38.34), and 1277.95 (range, 238.37–10341.04), respectively. Patients with SUVmax less than or equal to 16.9 showed significantly worse RFS than patients with SUVmax greater than 16.9 (5-year RFS rate: 60% vs. 100%, p = 0.008). Patients with SUVmax less than or equal to 16.9 showed significantly worse OS than patients with SUVmax greater than 16.9 (5-year OS rate: 80% vs. 100% p = 0.042).

Conclusion

Higher SUVmax at pretreatment ¹⁸F-FDG PET/CT was associated with better relapse free survival and overall survival in DLBCL patients after consolidation therapy with ¹³¹I-rituximab. However, because this study has a small number of patients, a phase 3 study with a larger number of patients is needed for clinical application in the future.

Enhanced CT-based radiomics predicts pathological complete response after neoadjuvant chemotherapy for advanced adenocarcinoma of the esophagogastric junction: a two-center study

Purpose

This study aimed to develop and validate CT-based models to predict pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) for advanced adenocarcinoma of the esophagogastric junction (AEG).

Methods

Pre-NAC clinical and imaging data of AEG patients who underwent surgical resection after preoperative-NAC at two centers were retrospectively collected from November 2014 to September 2020. The dataset included training (n = 60) and external validation groups (n = 32). Three models, including CT-based radiomics, clinical and radiomics–clinical combined models, were established to differentiate pCR (tumor regression grade (TRG) = grade 0) and nonpCR (TRG = grade 1–3) patients. For the radiomics model, tumor-region-based radiomics features in the arterial and venous phases were extracted and selected. The naïve Bayes classifier was used to establish arterial- and venous-phase radiomics models. The selected candidate clinical factors were used to establish a clinical model, which was further incorporated into the radiomics–clinical combined model. ROC analysis, calibration and decision curves were used to assess the model performance.

Results

For the radiomics model, the AUC values obtained using the venous data were higher than those obtained using the arterial data (training: 0.751 vs. 0.736; validation: 0.768 vs. 0.750). Borrmann typing, tumor thickness and degree of differentiation were utilized to establish the clinical model (AUC-training: 0.753; AUC-validation: 0.848). The combination of arterial- and venous-phase radiomics and clinical factors further improved the discriminatory performance of the model (AUC-training: 0.838; AUC-validation: 0.902). The decision curve reflects the higher net benefit of the combined model.

Conclusion

The combination of CT imaging and clinical factors pre-NAC for advanced AEG could help stratify potential responsiveness to NAC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13244-022-01273-w.

Relationship between total lesion glycolysis of primary lesions based on 18F-FDG PET/CT and lymph node metastasis in gastric adenocarcinoma: a cross-sectional preliminary study

OBJECTIVES

We explored the relationship between lymph node metastasis (LNM) and total lesion glycolysis (TLG) of primary lesions determined by 18fluoro-2-deoxyglucose PET/computed tomography (18F-FDG PET/CT) in patients with gastric adenocarcinoma, and evaluated the independent effect of this association.

METHODS

This retrospective study included 106 gastric adenocarcinoma patients who were examined by preoperative 18F-FDG PET/CT imaging between April 2016 and April 2020. We measured TLG of primary gastric lesions and evaluated its association with LNM. Multivariate logistic regression and a two-piece-wise linear regression were performed to evaluate the relationship between TLG of primary lesions and LNM.

RESULTS

Of the 106 patients, 75 cases (71%) had LNM and 31 cases (29%) did not have LNM. Univariate analyses revealed that a per-SD increase in TLG was independently associated with LNM [odds ratio (OR) = 2.37; 95% confidence interval (CI), 1.42-3.98; P = 0.0010]. After full adjustment of confounding factors, multivariate analyses exhibited that TLG of primary lesions was still significantly associated with LNM (OR per-SD: 2.20; 95% CI, 1.16-4.19; P = 0.0164). Generalized additive model indicated a nonlinear relationship and saturation effect between TLG of primary lesions and LNM. When TLG of primary lesions was <23.2, TLG was significantly correlated with LNM (OR = 1.26; 95% CI, 1.07-1.48; P = 0.0053), whereas when TLG of primary lesions was ≥ 23.2, the probability of LNM was greater than 60%, gradually reached saturation effect, as high as 80% or more.

CONCLUSIONS

In this preliminary study, there were saturation and segmentation effects between TLG of primary lesions determined by preoperative 18F-FDG PET/CT and LNM. When TLG of primary lesions was ≥ 23.2, the probability of LNM was greater than 60%, gradually reached saturation effect, as high as 80% or more. TLG of primary lesions is helpful in the preoperative diagnosis of LNM in patients with gastric adenocarcinoma.

Development and evaluation of a ceMDCT-based preoperative risk stratification model to predict disease-free survival after radical surgery in patients with gastric cancer

PURPOSE

To develop and evaluate a preoperative risk stratification model for predicting disease-free survival (DFS) based on contrast-enhanced multidetector computed tomography (ceMDCT) images in patients with gastric cancer (GC) undergoing radical surgery.

METHODS

We retrospectively enrolled patients with GC who underwent ceMDCT followed by radical surgery. A preoperative risk stratification model was constructed (including risk factor selection, risk status scoring, and risk level assignment) using Cox proportional hazard regression and log-rank analyses in the training cohort; the model was tested in the validation cohort. A nomogram was used to compare the preoperative risk stratification model with a postoperative DFS prediction model.

RESULTS

A total of 462 patients (training/validation: 271/191) were included. The ceMDCT features of T category (score of 0 or 2), N category (0, 1, 2, or 3), extramural vessel invasion (0 or 2), and tumor location (0 or 1) were selected to construct the preoperative risk stratification model, with 4 risk levels defined based on risk score. There were significant differences in DFS among the risk levels in both cohorts (p < 0.001). The predictive value of the preoperative model was similar to that of the postoperative model, with concordance indices of 0.791 (95% CI, 0.743-0.837) and 0.739 (95% CI, 0.666-0.812), respectively, in the training cohort and 0.762 (95% CI, 0.696-0.828) and 0.738 (95% CI, 0.684-0.792), respectively, in the validation cohort.

CONCLUSION

A preoperative risk stratification model based on ceMDCT images could be used to predict DFS and thus classify GC cases into various risk levels.

Dual-Energy CT-Based Nomogram for Decoding HER2 Status in Patients With Gastric Cancer

OBJECTIVE. The purpose of this study was to develop and evaluate a dual-energy CT (DECT)-based nomogram for noninvasive identification of the status of human epidermal growth factor receptor 2 (HER2; also known as ERBB2) expression in gastric cancer (GC). MATERIALS AND METHODS. A total of 206 patients with histologically proven GC who underwent pretreatment DECT were retrospectively recruited and randomly allocated to a training cohort (n = 144) or a test cohort (n = 62). Information on clinical characteristics, qualitative imaging features, and quantitative DECT parameters was collected. Univariate analysis and multivariate logistic regression were implemented to screen independent predictors of HER2 status. An individualized nomogram was built, and its discrimination, calibration, and clinical usefulness were assessed. RESULTS. Tumor location, the iodine concentration of the tumor in the venous phase, and the normalized iodine concentration of the tumor in the venous phase were significant factors predictive of HER2 status (all p < .05). After these three indicators were integrated, the proposed nomogram showed a favorable diagnostic performance, with AUCs of 0.807 (95% CI, 0.718-0.897) in the training cohort and 0.815 (95% CI, 0.661-0.968) in the test cohort. The nomogram showed a preferable fitting (all p > .05 by the Hosmer-Lemeshow test) and would offer more net benefits than simple default strategies within a wide range of threshold probabilities in both cohorts. CONCLUSION. The DECT-based nomogram has great application potential in terms of detecting HER2 status in GC, and can serve as a novel substitute for invasive testing.

Intra-tumor metabolic heterogeneity of gastric cancer on 18F-FDG PETCT indicates patient survival outcomes

The present study aimed to investigate the prognostic value of intra-tumor metabolic heterogeneity on 2-[18F] Fluoro-2-deoxy-D-glucose (¹⁸F-FDG) positron emission tomography/computed tomography (PET/CT) for patients with gastric cancer. Fifty-five patients with advanced gastric cancer that had received neoadjuvant chemotherapy and radical surgery were included. Clinicopathological information, ¹⁸F-FDG PET/CT before chemotherapy, pathological response, recurrence or metastasis, progression-free survival (PFS), and overall survival (OS) of the patients were collected. The maximum, peak, and mean standardized uptake values (SUV_max, SUV_peak, and SUV_mean), tumor-to-liver ratio (TLR), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) on PET/CT were measured. Heterogeneity index-1 (HI-1) was calculated as SUV_mean divided by the standard deviation, and heterogeneity index-2 (HI-2) was evaluated through linear regressions of MTVs according to different SUV thresholds. Associations between these parameters and patient survival outcomes were analyzed. None of the parameters on PET were associated with tumor recurrence. Pathological responders had significantly smaller TLR, MTV and HI-2 values than non-responders (P = 0.017, 0.017 and 0.013, respectively). In multivariate analysis of PFS, only HI-2 was an independent factor (hazard ratio [HR] = 2.693, P = 0.005) after adjusting for clinical tumor-node-metastasis (TNM) stage. In multivariate analysis of OS, HI-2 was also an independent predictive factor (HR = 2.281, P = 0.009) after adjusting for tumor recurrence. Thus, HI-2 generated from baseline ¹⁸F-FDG PET/CT is significantly associated with survival of patients with gastric cancer. Preoperative assessment of HI-2 by ¹⁸F-FDG PET/CT might be promising to identify patients with poor prognosis.

18F-Fluorodeoxyglucose Positron Emission Tomography-Computed Tomography Metabolic Parameters Before and After Neoadjuvant Chemotherapy Can Predict the Postoperative Prognosis of Locally Advanced Gastric Cancer

Objective: To explore the value of ¹⁸F-fluorodeoxyglucose positron emission tomography-computed tomography (¹⁸F-FDG PET/CT) metabolic parameters before and after neoadjuvant chemotherapy in predicting histopathological response and prognosis of locally advanced gastric cancer. Materials and Methods: A total of 56 patients with locally advanced gastric cancer underwent ¹⁸F-FDG PET/CT before and after neoadjuvant chemotherapy. The maximum standardized uptake value (SUV_max), mean standardized uptake value (SUV_mean), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) of the lesions were measured before and after neoadjuvant chemotherapy. The percentage changes in the maximum standardized uptake value (ΔSUV_max%), mean standardized uptake value (ΔSUV_mean%), metabolic tumor volume (ΔMTV%), and total lesion glycolysis (ΔTLG%), which were derived from ¹⁸F-FDG PET/CT, were calculated, and the cutoff values were determined by receiver operating characteristic curve analysis. Differences in progression-free survival (PFS) and overall survival (OS) between groups dichotomized by these cutoffs were analyzed using the Kaplan-Meier method and Cox proportional hazards regression model. Results: The patients were divided into histopathological responders and nonresponders according to the following cutoff values: 58.8% SUV_max reduction, 45.8% SUV_mean reduction, 36.9% MTV reduction, and 57.8% TLG reduction. The differences in PFS and OS between groups dichotomized by these cutoffs were significant (all p < 0.01). Multivariate analysis suggested that a ΔTLG% > 57.8% was an independent postoperative risk factor for PFS (hazard ratio [HR] 0.348, 95% confidence interval [CI] 0.131-0.926, p = 0.035) and OS (HR 0.107, 95% CI 0.023-0.498, p = 0.004). Conclusions: The metabolic parameters before and after neoadjuvant chemotherapy of ¹⁸F-FDG PET/CT accurately reflected the chemotherapy effect, and ΔTLG% was the only independent postoperative predictive factor of PFS and OS for locally advanced gastric cancer.

Identification of specific modules and hub genes associated with the progression of gastric cancer

Gastric cancer (GC) has high morbidity and mortality rates worldwide. Abundant literature has reported several individual genes and their related pathways intimately involved in tumor progression. However, little is known about GC progression at the gene network level. Therefore, understanding the underlying mechanisms of pathological transition from early stage to late stage is urgently needed. This study aims to identify potential vital genes and modules involved in the progression of GC. To understand the gene regulatory network of GC progression, we analyzed micro RNAs and messenger RNA s expression profiles by using a couple of bioinformatics tools. miR-205 was identified by differentially expressed analysis and was further confirmed through using multiple kernel learning-based Kronecker regularized least squares. Using weighted gene co-expression network analysis, the gastric cancer progression-related module, which has the highest correlation value with cancer progression, was obtained. Kyoto Encyclopedia of Genes and Genomes pathways and biological processes of the GCPR module genes were related to cell adhesion. Meanwhile, large-scale genes of GCPR module were found to be targeted by miR-205, including two hub genes SORBS1 and LPAR1. In brief, through multiple analytical methods, we found that miR-205 and the GCPR module play critical roles in GC progression. In addition, miR-205 might maintain cell adhesion by regulating SORBS1 and LPAR1. To screen the potential drug candidates, the gene expression profile of the GCPR module was mapped connectivity map (Cmap), and the mTOR inhibitor (Sirolimus) was found to be the most promising candidate. We further confirmed that Sirolimus can suppress cell proliferation of GC cell in vitro.

Low metabolic activity in primary gastric adenocarcinoma is associated with resistance to chemoradiation and the presence of signet ring cells

PURPOSES

Preoperative chemoradiation is a potential treatment option for localized gastric adenocarcinoma (GAC). Currently, the response to chemoradiation cannot be predicted. We analyzed the pretreatment maximum standardized uptake value (SUV_max) and total lesion glycolysis (TLG) on positron emission tomography/computed tomography as potential predictors of the response to chemoradiation.

METHODS

We analyzed the SUV_max and TLG data from 59 GAC patients who received preoperative chemoradiation. We used logistic regression models to predict a pathologic complete response (pCR) and Kaplan-Meier curves to determine overall survival among patients with high and low SUV_max or TLG.

RESULTS

Twenty-nine patients (49%) had Siewert type III adenocarcinoma and 30 (51%) had tumors located in the lower stomach. Forty-one patients had poorly differentiated GAC, and 26 had signet ring cells. The median SUV_max was 7.3 (0-28.2) and the median TLG was 56.6 (0-1881.5). Patients with signet ring cells had a low pCR rate, as well as a low SUV_max and TLG. In the multivariable logistic regression model, high SUV_max was a predictor of pCR (odds ratio = 11.1, 95% confidence interval = 2.12-50.0, p = 0.004). Overall survival was not associated with the SUV_max (log-rank p = 0.69) or TLG (log-rank p = 0.85) CONCLUSION: A high SUV_max was associated with sensitivity to chemoradiation and pCR in GAC, and signet ring cells seemed to confer resistance.

Nomogram using F-18 fluorodeoxyglucose positron emission tomography/computed tomography for preoperative prediction of lymph node metastasis in gastric cancer

BACKGROUND

Lymph node (LN) metastasis is an important prognostic factor in patients with gastric cancer (GC). However, the evaluation of LN metastasis status in the preoperative setting is not accurate. Therefore, precise preoperative prediction of LN metastasis status is crucial for optimal treatment in patients with GC.

AIM

To develop a preoperative nomogram for LN metastasis using F-18 fluorodeoxyglucose (F-18 FDG) positron emission tomography/computed tomography (PET/CT) and preoperative laboratory test findings in GC.

METHODS

In this study, the data of 566 GC patients who underwent preoperative F-18 FDG PET/CT and subsequent surgical resection were analyzed. The LN metastasis prediction model was developed in the training cohort and validated in the internal validation cohort. Routine preoperative laboratory tests, including albumin and carbohydrate antigen (CA) 19-9 were performed in all patients. Univariate and multivariable logistic regression was performed to validate the preoperative predictive indicators for LN metastasis.

RESULTS

Of the 566 patients, 232 (41%) had confirmed histopathologic LN metastasis. Univariate logistic regression revealed that the tumor location, blood hemoglobin, serum albumin levels, neutrophil to lymphocyte ratio, platelet to lymphocyte ratio, CA 19-9, maximum standardized uptake value (SUVmax) of the primary tumor (T_SUVmax), and SUVmax of LN (N_SUVmax) were significantly associated with LN metastasis. In multivariate analysis, T_SUVmax (OR = 1.08; 95%CI: 1.02–1.15; P = 0.011) and N_SUVmax (OR = 1.49; 95%CI: 1.19–1.97; P = 0.002) were found to be significant predictive factors for LN metastasis. The LN metastasis prediction model using T_SUVmax, N_SUVmax, serum albumin, and CA 19-9 yielded an area under the curve (AUC) of 0.733 (95%CI: 0.683–0.784, P = 0.025) in the training cohort and AUC of 0.756 (95%CI: 0.678–0.833, P < 0.001) in the test cohort.

CONCLUSION

T_SUVmax and N_SUVmax measured by preoperative F-18 FDG PET/CT are independent predictive factors for LN metastasis in GC.

Gastric cancer and image-derived quantitative parameters: Part 2-a critical review of DCE-MRI and 18F-FDG PET/CT findings

Abstract

There is yet no consensus on the application of functional imaging and qualitative image interpretation in the management of gastric cancer. In this second part, we will discuss the role of image-derived quantitative parameters from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) in gastric cancer, as both techniques have been shown to be promising and useful tools in the clinical decision making of this disease. We will focus on different aspects including aggressiveness assessment, staging and Lauren type discrimination, prognosis prediction and response evaluation. Although both the number of articles and the patients enrolled in the studies were rather small, there is evidence that quantitative parameters from DCE-MRI such as K^trans, V_e, K_ep and AUC could be promising image-derived surrogate parameters for the management of gastric cancer. Data from ¹⁸F-FDG PET/CT studies showed that standardised uptake value (SUV) is significantly associated with the aggressiveness, treatment response and prognosis of this disease. Along with the results from diffusion-weighted MRI and contrast-enhanced multidetector computed tomography presented in Part 1 of this critical review, there are additional image-derived quantitative parameters from DCE-MRI and ¹⁸F-FDG PET/CT that hold promise as effective tools in the diagnostic pathway of gastric cancer.

Key Points

• Quantitative analysis from DCE-MRI and¹⁸F-FDG PET/CT allows the extrapolation of multiple image-derived parameters.

• Data from DCE-MRI (K^trans, V_e, K_ep and AUC) and ¹⁸F-FDG PET/CT (SUV) are non-invasive, quantitative image-derived parameters that hold promise in the evaluation of the aggressiveness, treatment response and prognosis of gastric cancer.

Predictive Role of Temporal Changes in Intratumoral Metabolic Heterogeneity During Palliative Chemotherapy in Patients with Advanced Pancreatic Cancer: A Prospective Cohort Study

Metabolic intratumoral heterogeneity (ITH) is known to be related to cancer treatment outcome. However, information on the temporal changes in metabolic ITH during chemotherapy and the correlations between metabolic changes and treatment outcomes in patients with pancreatic cancer is sparse. We aimed to analyze the temporal changes in metabolic ITH and the predictive role of its changes in advanced pancreatic cancer patients who underwent palliative chemotherapy. Methods: We prospectively enrolled patients with unresectable locally advanced or metastatic pancreatic cancer before first-line palliative chemotherapy. ¹⁸F-FDG PET was performed at baseline and at the first response follow-up. SUVs, volumetric parameters, and textural features of the primary pancreatic tumor were analyzed. Relationships between the parameters at baseline and first follow-up were assessed, as well as changes in the parameters with treatment response, progression-free survival (PFS), and overall survival (OS). Results: Among 63 enrolled patients, the best objective response rate was 25.8% (95% confidence interval [CI], 14.6%-37.0%). The median PFS and OS were 7.1 mo (95% CI, 5.1-9.7 mo) and 10.1 mo (95% CI, 8.6-12.7 mo), respectively. Most parameters changed significantly during the first-line chemotherapy, in a way of reducing ITH. Metabolic ITH was more profoundly reduced in responders than in nonresponders. Multiple Cox regression analysis identified high baseline compacity (P = 0.023) and smaller decreases in SUV_peak (P = 0.007) and entropy gray-level cooccurrence matrix (P = 0.033) to be independently associated with poor PFS. Patients with a high carbohydrate antigen 19-9 (P = 0.042), high pretreatment SUV_peak (P = 0.008), and high coefficient of variance at first follow-up (P = 0.04) showed worse OS. Conclusion: Reduction in metabolic ITH during palliative chemotherapy in advanced pancreatic cancer patients is associated with treatment response and might be predictive of PFS and OS.

Expression of transmembrane protein 41A is associated with metastasis via the modulation of E‑cadherin in radically resected gastric cancer

Gastric cancer (GC) is one of the most commonly occurring malignancies worldwide, and metastasis is one of the key processes affecting the prognosis of GC. TMEM41A, which belongs to a group of transmembrane proteins that participate in signaling pathways and tumor development, is a 264‑amino acid protein encoded by a gene mapped to human chromosome The exact role of TMEM41A in GC has not been determined to date. In the present study, the expression of TMEM41A in 147 cases of GC was analyzed with immunohistohemistry and the prognoses of these patients were analyzed. It was revealed that TMEM41A was highly expressed in GC tissues, and may be associated with the progression of GC and poor prognosis. The expression of TMEM41A was observed to be correlated with lymph node metastasis, distant metastasis and advanced tumor, node and metastasis stages. Knockdown of TMEM41A in vitro and in vivo decreased the GC cell migration ability by regulating epithelial‑to‑mesenchymal transition and cell autophagy, via the upregulation of E‑cadherin and downregulating N‑cadherin expression in GC cells by reverse transcription‑quantitative polymerase chain reaction (PCR), semi‑PCR and western blotting. Furthermore, TMEM41A upregulation was associated with the upregulation of p62 and altered the conversion of light chain (LC)3‑1 into LC3‑2 by western blotting. Knockdown of TMEM41A was also observed to affect tumor metastasis in nude mice. Therefore, TMEM41A may be considered as a novel therapeutic target for the treatment of GC‑associated metastasis.

Tumoral vascular pattern in renal cell carcinoma and fat-poor renal angiomyolipoma as a novel helpful differentiating factor on contrast-enhanced CT scan

Our objective was to evaluate the differences between tumoral vascular pattern of renal cell carcinoma and fat-poor angiomyolipoma by contrast-enhanced computed tomography. All included patients had a definitive pathological diagnosis of either angiomyolipoma or renal cell carcinoma, and then the contrast-enhanced computed tomography images of these patients were evaluated. The patients who had visible prominent vessels in cross-sectional imaging were selected. The tumor vascular pattern (prominent (>2 mm) intratumoral and peritumoral vessels), density, and diameter of the vessels in renal cell carcinoma and fat-poor angiomyolipoma were evaluated. All cases (n = 12) with fat-poor angiomyolipoma were found to have intratumoral vessels and all cases (n = 36) with clear cell renal cell carcinoma were found to have peritumoral vessels. There was no significant correlation detected between the diameter of tumor and the density as well as diameter of the vessels. In conclusion, the evaluation of the vascular pattern using contrast enhancement contrast-enhanced computed tomography may provide important information that is useful in helping accurate differential diagnosis of fat-poor angiomyolipoma or renal cell carcinoma preoperatively.