Response to chemotherapy in gastric adenocarcinoma with diffusion-weighted MRI and (18) F-FDG-PET/CT: correlation of apparent diffusion coefficient and partial volume corrected standardized uptake value with histological tumor regression grade

The Chinese Society of Clinical Oncology (CSCO): Clinical guidelines for the diagnosis and treatment of gastric cancer, 2023

The 2023 update of the Chinese Society of Clinical Oncology (CSCO) Clinical Guidelines for Gastric Cancer focuses on standardizing cancer diagnosis and treatment in China, reflecting the latest advancements in evidence-based medicine, healthcare resource availability, and precision medicine. These updates address the differences in epidemiological characteristics, clinicopathological features, tumor biology, treatment patterns, and drug selections between Eastern and Western gastric cancer patients. Key revisions include a structured template for imaging diagnosis reports, updated standards for molecular marker testing in pathological diagnosis, and an elevated recommendation for neoadjuvant chemotherapy in stage III gastric cancer. For advanced metastatic gastric cancer, the guidelines introduce new recommendations for immunotherapy, anti-angiogenic therapy and targeted drugs, along with updated management strategies for human epidermal growth factor receptor 2 (HER2)-positive and deficient DNA mismatch repair (dMMR)/microsatellite instability-high (MSI-H) patients. Additionally, the guidelines offer detailed screening recommendations for hereditary gastric cancer and an appendix listing drug treatment regimens for various stages of gastric cancer. The 2023 CSCO Clinical Guidelines for Gastric Cancer updates are based on both Chinese and international clinical research and expert consensus to enhance their applicability and relevance in clinical practice, particularly in the heterogeneous healthcare landscape of China, while maintaining a commitment to scientific rigor, impartiality, and timely revisions.

Imaging advances in efficacy assessment of gastric cancer neoadjuvant chemotherapy

Effective neoadjuvant chemotherapy (NAC) can improve the survival of patients with locally progressive gastric cancer, but chemotherapeutics do not always exhibit good efficacy in all patients. Therefore, accurate preoperative evaluation of the effect of neoadjuvant therapy and the appropriate selection of surgery time to minimize toxicity and complications while prolonging patient survival are key issues that need to be addressed. This paper reviews the role of three imaging methods, morphological, functional, radiomics, and artificial intelligence (AI)-based imaging, in evaluating NAC pathological reactions for gastric cancer. In addition, the advantages and disadvantages of each method and the future application prospects are discussed.

Dynamic contrast-enhanced and diffusion-weighted MR imaging in early prediction of pathologic response to neoadjuvant chemotherapy in locally advanced gastric cancer

PURPOSE

To investigate the efficacy of diffusion-weighted imaging (DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for the early prediction of the pathologic response to neoadjuvant chemotherapy (NAC) in patients with locally advanced gastric cancer (LAGC).

METHODS

Fifty patients with LAGC who were treated with NAC followed by radical gastrectomy were enrolled. Uncontrasted and DCE-MRI were performed within 1 week before NAC. According to tumor regression grading (TRG), patients were labeled as responders (TRG = 0 + 1) and non-responders (TRG = 2 + 3). Apparent diffusion coefficients (ADC) and DCE-MRI kinetics (K^trans, V_e, and K_ep) were compared between the two groups. Logistic regression analysis was performed to screen independent factors to predict the NAC efficacy. The relationship between MRI parameters and TRG was studied by Spearman's correlation analysis. Receiver-operating characteristic curve analyses were applied to evaluate the efficacy.

RESULTS

ADC, K^trans, and K_ep values were higher in responders than in non-responders (p < 0.05) and correlated with TRG (p < 0.05). The ADC and K_ep values were independent markers for predicting TRG. The area under the curve, sensitivities, specificities of ADC, K^trans, K_ep, and ADC + K_ep were 0.813, 0.699, 0.709, 0.886;73.64%, 65.54%, 63.21%, 70.37%; 86.47%, 54.97%, 79.47%, 95.65%; respectively. ADC + K_ep demonstrated a higher efficacy than K^trans and K_ep (p = 0.012, 0.011), but without improvement compared with ADC (p > 0.05).

CONCLUSION

Both DWI and DCE-MRI can effectively predict the pathologic response to NAC in LAGC. A combination of ADC and K_ep increased the efficacy, and ADC is the most valuable imaging parameter.

Application of nanotechnology in the early diagnosis and comprehensive treatment of gastrointestinal cancer

Gastrointestinal cancer (GIC) is a common malignant tumour of the digestive system that seriously threatens human health. Due to the unique organ structure of the gastrointestinal tract, endoscopic and MRI diagnoses of GIC in the clinic share the problem of low sensitivity. The ineffectiveness of drugs and high recurrence rates in surgical and drug therapies are the main factors that impact the curative effect in GIC patients. Therefore, there is an urgent need to improve diagnostic accuracies and treatment efficiencies. Nanotechnology is widely used in the diagnosis and treatment of GIC by virtue of its unique size advantages and extensive modifiability. In the diagnosis and treatment of clinical GIC, surface-enhanced Raman scattering (SERS) nanoparticles, electrochemical nanobiosensors and magnetic nanoparticles, intraoperative imaging nanoparticles, drug delivery systems and other multifunctional nanoparticles have successfully improved the diagnosis and treatment of GIC. It is important to further improve the coordinated development of nanotechnology and GIC diagnosis and treatment. Herein, starting from the clinical diagnosis and treatment of GIC, this review summarizes which nanotechnologies have been applied in clinical diagnosis and treatment of GIC in recent years, and which cannot be applied in clinical practice. We also point out which challenges must be overcome by nanotechnology in the development of the clinical diagnosis and treatment of GIC and discuss how to quickly and safely combine the latest nanotechnology developed in the laboratory with clinical applications. Finally, we hope that this review can provide valuable reference information for researchers who are conducting cross-research on GIC and nanotechnology.

Tumor-Targeted Polydopamine-Based Nanoparticles for Multimodal Mapping Following Photothermal Therapy of Metastatic Lymph Nodes

Purpose

Lymphadenectomy with lymph node (LN) mapping is essential for surgical removal of solid tumors. Existing agents do not provide accurate multimodal mapping and antitumor therapy for metastatic LNs; therefore, we fabricated a polydopamine (PDA) nanoparticle (NP)-based tumor-targeted LN mapping agent capable of multimodal mapping and guided photothermal therapy (PTT) for metastatic LNs.

Materials and Methods

PDA NPs modified with polyethylene glycol (PEG) were obtained by polymerization under alkaline conditions. The PEG-PDA NPs were loaded with the circular tripeptide Arg-Gly-Asp (cRGD) to achieve tumor-targeting capacity and with the fluorescent dye IR820 and magnetic resonance imaging (MRI) contrast Gd(NH₂)₂ for in situ detection. The resulting cRGD-PEG-PDA@IR820/Gd(NH₂)₂ (cRGD-PPIG) NPs were tested for their biosafety and metastatic LN mapping ability. They were drained specifically into LNs and selectively taken up by gastric MKN45 cells via α_vβ3 integrin-mediated endocytosis.

Results

This phenomenon enabled MR/optical/near-infrared fluorescence multimodal metastatic LN mapping, guiding the creation of accurate and highly efficient PTT for gastric cancer metastatic LNs in mice.

Conclusion

In summary, we fabricated tumor-targeted cRGD-PPIG NPs with MR/optical/near-infrared fluorescence multimodal metastatic LN mapping capacity for surgery and efficient PTT guidance post-surgery.

The Chinese Society of Clinical Oncology (CSCO): Clinical guidelines for the diagnosis and treatment of gastric cancer, 2021

There exist differences in the epidemiological characteristics, clinicopathological features, tumor biological characteristics, treatment patterns, and drug selections between gastric cancer patients from the Eastern and Western countries. The Chinese Society of Clinical Oncology (CSCO) has organized a panel of senior experts specializing in all sub-specialties of gastric cancer to compile a clinical guideline for the diagnosis and treatment of gastric cancer since 2016 and renews it annually. Taking into account regional differences, giving full consideration to the accessibility of diagnosis and treatment resources, these experts have conducted expert consensus judgment on relevant evidence and made various grades of recommendations for the clinical diagnosis and treatment of gastric cancer to reflect the value of cancer treatment and meeting health economic indexes in China. The 2021 CSCO Clinical Practice Guidelines for Gastric Cancer covers the diagnosis, treatment, follow-up, and screening of gastric cancer. Based on the 2020 version of the CSCO Chinese Gastric Cancer guidelines, this updated guideline integrates the results of major clinical studies from China and overseas for the past year, focused on the inclusion of research data from the Chinese population for more personalized and clinically relevant recommendations. For the comprehensive treatment of non-metastatic gastric cancer, attentions were paid to neoadjuvant treatment. The value of perioperative chemotherapy is gradually becoming clearer and its recommendation level has been updated. For the comprehensive treatment of metastatic gastric cancer, recommendations for immunotherapy were included, and immune checkpoint inhibitors from third-line to the first-line of treatment for different patient groups with detailed notes are provided.

Tumor-Associated Macrophages in Hepatocellular Carcinoma: Friend or Foe?

Hepatocellular carcinoma (HCC) is one of the most common malignancies worldwide, and it has diverse etiologies with multiple mechanisms. The diagnosis of HCC typically occurs at advanced stages when there are limited therapeutic options. Hepatocarcinogenesis is considered a multistep process, and hepatic macrophages play a critical role in the inflammatory process leading to HCC. Emerging evidence has shown that tumor-associated macrophages (TAMs) are crucial components defining the HCC immune microenvironment and represent an appealing option for disrupting the formation and development of HCC. In this review, we summarize the current knowledge of the polarization and function of TAMs in the pathogenesis of HCC, as well as the mechanisms underlying TAM-related anti-HCC therapies. Eventually, novel insights into these important aspects of TAMs and their roles in the HCC microenvironment might lead to promising TAM-focused therapeutic strategies for HCC.

Role of CT in the prediction of pathological complete response in gastric cancer after neoadjuvant chemotherapy

OBJECTIVE

To explore which computed tomography (CT) features can predict pathological complete response (pCR) (ypT0N0) after neoadjuvant chemotherapy (NAC) in patients with gastric adenocarcinoma (GC).

MATERIALS AND METHODS

This study reviewed an institutional database of patients who underwent resection of GC after NAC and identified patients with pCR from January 2010 to December 2013. The correlations between pre-chemotherapy and post-chemotherapy CT features and pCR were analyzed.

RESULTS

Eleven of 199 patients with GC who achieved ypT0N0 status after NAC were classified as the pCR group in this study. After matching pCR (n = 11) and non-pCR patients (n = 44) in the ratio of 1:4, a total of 55 cases were analyzed. The binary logistic regression analysis showed that the post-chemotherapy short diameter of the largest lymph node and tumor thickness ratio reduction were independent predictors of pCR, with an area under the curve (AUC) of 0.94 on the receiver operating characteristic (ROC) curve analysis.

CONCLUSION

Two CT features, including the short diameter of the largest lymph node post-chemotherapy and tumor thickness ratio reduction, are good predictors of pCR after NAC in patients with GC.

Quantitative study of preoperative staging of gastric cancer using intravoxel incoherent motion diffusion-weighted imaging as a potential clinical index

PURPOSE

To determine the utility of intravoxel incoherent motion (IVIM) diffusion-weighted imaging in quantitative analysis of preoperative tumor (T) and node (N) stages of gastric cancer, and to quantify the diagnostic threshold of IVIM parameters for serosal invasion and lymphatic metastasis.

MATERIALS AND METHODS

From October 2016 to February 2020, 98 patients with gastric cancer who were receiving treatment in Zhongshan Hospital, China, were subject to an IVIM sequence imaging analysis. The IVIM sequence data were imported into software for post-processing of tumor regions of interest, and the IVIM parameters (the microvascular volume fraction (f), the molecular diffusion coefficient (D) and perfusion-related incoherent microcirculation (D*) were calculated. The variation of these IVIM parameters with different tumor-node metastasis (TNM) stages were analyzed by one-way analysis of variance. The IVIM parameters of serosal invasion and lymphatic metastasis were examined by receiver operating characteristic curve analysis and t-tests.

RESULTS

A total of 98 gastric cancer patients (65 males and 33 females) with an average age of 61.9 years were enrolled in this study. There were 14 patients in stage T1, 14 in stage T2, 10 in stage T3 and 60 in stage T4_a+b. There were 37 patients in stage N0, 19 in stage N1, 18 in stage N2 and 24 in stage N3. Statistically significant associations were found between the D values and T stages of gastric cancer. The D values of stage T4 cancers were significantly different from those of stage T2, T3 and T4 cancers. The D value decreased with increasing T stage. The mean D values of stages were 1.432 × 10^-3 mm²/s (T1), 1.225 × 10^-3 mm²/s (T2), 1.154 × 10^-3 mm²/s (T3) and 0.9468 × 10^-3 mm²/s (T4). The extent of the invasion of serosa was found to be significantly correlated with D value, with the diagnostic threshold for D being 1.107 × 10^-3 mm²/s. In addition, different pathological N stages of gastric cancer lesions showed statistically significantly variations in f values, but no correlation was found with different N stages. Finally, the extent of lymphatic metastasis was found to be correlated with D values, with the diagnostic threshold being 1.1739 × 10^-3 mm²/s. There was no statistically significant correlation between the IVIM MRI parameters and tumor size. The grade of tumor was found to be significantly correlated with D* value, with the diagnostic threshold for D* being 1.516 × 10^-2 mm²/s. There was no statistically significant correlation between the ADC value and tumor size. There was a significant difference in the ADC values among different T and N stage cancers. ADC value had statistically significant to distinguish gastric cancer with or without serosal invasion, its detection efficiency was not as high as that of D value, with an AUC of 0.628 and 0.830, respectively. The ADC value was not statistically significant in distinguishing gastric cancer with or without lymphatic metastasis (P ≥ 0.05). The ADC value had not statistically significant in distinguishing gastric cancer between low and medium-high grade (P ≥ 0.05).

CONCLUSION

We found that significant differences existed between whole-volume IVIM parameters of different T or N stages in gastric cancers, and were able to quantify different T or N stages of gastric cancer by the values of these parameters. The results of this quantitative study provide new tools for evaluating the prognosis of gastric cancer and will be valuable for the development of an new imaging method for determining the morphological stages of gastric cancer.

Prediction of tumour grade and survival outcome using pre-treatment PET- and MRI-derived imaging features in patients with resectable pancreatic ductal adenocarcinoma

OBJECTIVES

To perform a correlation analysis between histopathology and imaging in patients with previously untreated pancreatic ductal adenocarcinoma (PDAC) and to determine the prognostic values of clinical, histological, and imaging parameters regarding overall survival (OS), disease-specific survival (DSS), and progression-free survival (PFS).

METHODS

This single-centre study prospectively included 61 patients (32 males; median age, 68.0 years [IQR, 63.0-75.0 years]) with histologically confirmed PDAC and following surgical resection who preoperatively underwent ¹⁸F-FDG PET/CT and DW-MRI. On whole lesions, we measured, using a 42% SUV_max threshold volume of interest (VOI), the following quantitative parameters: mean and maximum standardised uptake values (SUV_mean and SUV_max), total lesion glycolysis (TLG), metabolic tumour volume (MTV), mean and minimum apparent diffusion coefficient (ADC_mean and ADC_min), diffusion total volume (DTV), and MTV/ADC_min ratio. Spearman's correlation analysis was performed to assess relationships between these markers and histopathological findings from surgical specimens (stage; grade; resection quality; and vascular, perineural, and lymphatic invasion). Kaplan-Meier and Cox hazard ratio methods were used to evaluate the impacts of imaging parameters on OS (n = 41), DSS (n = 36), and PFS (n = 41).

RESULTS

Inverse correlations between ADC_min and SUV_max (rho = - 0.34; p = 0.0071), and between SUV_mean and ADC_mean (rho = - 0.29; p = 0.026) were identified. ADC_min was inversely correlated with tumour grade (rho = - 0.40; p = 0.0015). MTV was an independent predictive factor for OS and DSS, while DTV was an independent predictive factor for PFS.

CONCLUSION

In previously untreated PDAC, ADC and SUV values are correlated. Combining PET-MRI metrics may help predict PDAC grade and patients' survival.

KEY POINTS

• Minimum apparent diffusion coefficient derived from DW-MRI inversely correlates with tumour grade in pancreatic ductal adenocarcinoma. • In pancreatic ductal adenocarcinoma, metabolic tumour volume has been confirmed as a predictive factor for patients' overall survival and disease-specific survival. • Combining PET and MRI metrics may help predict grade and patients' survival in pancreatic ductal adenocarcinoma.

CT-based radiomics scores predict response to neoadjuvant chemotherapy and survival in patients with gastric cancer

BACKGROUND

Neoadjuvant chemotherapy is a promising treatment option for potential resectable gastric cancer, but patients' responses vary. We aimed to develop and validate a radiomics score (rad_score) to predict treatment response to neoadjuvant chemotherapy and to investigate its efficacy in survival stratification.

METHODS

A total of 106 patients with neoadjuvant chemotherapy before gastrectomy were included (training cohort: n = 74; validation cohort: n = 32). Radiomics features were extracted from the pre-treatment portal venous-phase CT. After feature reduction, a rad_score was established by Randomised Tree algorithm. A rad_clinical_score was constructed by integrating the rad_score with clinical variables, so was a clinical score by clinical variables only. The three scores were validated regarding their discrimination and clinical usefulness. The patients were stratified into two groups according to the score thresholds (updated with post-operative clinical variables), and their survivals were compared.

RESULTS

In the validation cohort, the rad_score demonstrated a good predicting performance in treatment response to the neoadjuvant chemotherapy (AUC [95% CI] =0.82 [0.67, 0.98]), which was better than the clinical score (based on pre-operative clinical variables) without significant difference (0.62 [0.42, 0.83], P = 0.09). The rad_clinical_score could not further improve the performance of the rad_score (0.70 [0.51, 0.88], P = 0.16). Based on the thresholds of these scores, the high-score groups all achieved better survivals than the low-score groups in the whole cohort (all P < 0.001).

CONCLUSION

The rad_score that we developed was effective in predicting treatment response to neoadjuvant chemotherapy and in stratifying patients with gastric cancer into different survival groups. Our proposed strategy is useful for individualised treatment planning.

Diffusion kurtosis imaging in the prediction of poor responses of locally advanced gastric cancer to neoadjuvant chemotherapy

PURPOSE

To assess the efficacy of diffusion kurtosis imaging (DKI) in the prediction of the treatment response to neoadjuvant chemotherapy in patients with locally advanced gastric cancer (LAGC).

METHODS

A total of 31 LAGC patients were enrolled in this prospective study. All patients underwent diffusion-weighted MRI examination (with b = 0₁, 200₁, 500₁, 800₂, 1000₄, 1500₄, 2000₆ s/mm², the subscript denotes the number of signal averages) before and after chemotherapy. DKI and mono-exponential (b = 0, 800 s/mm²) models were built. Apparent diffusion coefficient (ADC), mean diffusivity (MD) and mean kurtosis (MK) of the LAGC tumors were measured. The absolute change values (ΔX) and percentage change values (%ΔX) of the above parameters post neoadjuvant chemotherapy (NACT) were calculated. The response was evaluated according to the pathological tumor regression grade scores (effective response group: TRG 0-2, poor response group: TRG 3). Mann-Whitney U test and receiver operating characteristic (ROC) curves were applicated for statistical analysis.

RESULTS

There were 17 patients in the effective response group (ERG), and 14 patients in the poor response group (PRG). The MK_pre and MK_post values in PRG were significantly higher than those in ERG [(0.671 ± 0.026) and (0.641 ± 0.019) vs. (0.584 ± 0.023) and (0.519 ± 0.018), p < 0.001]. ADC_post and MD_post in PRG were significantly lower than those in ERG (p = 0.005, p =0.001). Significant differences were also observed for % ΔMK, ΔMD and ΔMK between the two groups (p < 0.05). The area under the curve (AUC) for the prediction of PRG was highest for MK_post (AUC = 0.958, cutoff value = 0.614). The MK_pre and MK_post had the highest sensitivity (91.70 %) and specificity (93.80 %) in the prediction of PRG, respectively.

CONCLUSION

Both DKI and ADC values show potential for the prediction of the PRG in LAGC patients. The DKI parameters, especially MK_post displayed the best performance.

The role of MRI in the diagnosis and treatment of gastric cancer

Gastric cancer is the fifth most common malignancies and the third leading cause of cancer-related death worldwide, with more than 40% of new cases occurring in China. With the advancement of treatment methods, the application of adjuvant therapy and targeted drugs, the prognosis of patients with gastric cancer has been significantly improved. In recent years, more and more studies have reported that magnetic resonance imaging (MRI) showed great value in the clinical application among patients with gastric cancer, including preoperative staging, treatment response evaluation, predicting prognosis and histopathological features, treatment guidance, and molecular imaging. The remarkable research progress of MRI in gastric cancer will provide new evaluation and treatment approaches for clinical diagnosis and treatment. This article aims to review the current status of the application and research progress of MRI in patients with gastric cancer.

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.

AI-based applications in hybrid imaging: how to build smart and truly multi-parametric decision models for radiomics

INTRODUCTION

The quantitative imaging features (radiomics) that can be obtained from the different modalities of current-generation hybrid imaging can give complementary information with regard to the tumour environment, as they measure different morphologic and functional imaging properties. These multi-parametric image descriptors can be combined with artificial intelligence applications into predictive models. It is now the time for hybrid PET/CT and PET/MRI to take the advantage offered by radiomics to assess the added clinical benefit of using multi-parametric models for the personalized diagnosis and prognosis of different disease phenotypes.

OBJECTIVE

The aim of the paper is to provide an overview of current challenges and available solutions to translate radiomics into hybrid PET-CT and PET-MRI imaging for a smart and truly multi-parametric decision model.

Predictive value of diffusion-weighted MR imaging in early response to chemoradiotherapy of esophageal cancer: a meta-analysis

The results of diffusion-weighted MR imaging (DW-MRI) in predicting early response to chemoradiotherapy in patients with esophageal cancer varied in different studies. We performed this meta-analysis to evaluate the predictive values of DW-MRI and compare the diagnostic efficacy of different apparent diffusion coefficients (ADCs). A comprehensive literature search was performed to identify relevant articles published before November 2017. The quality of study was assessed using Quality Assessment of Diagnostic Accuracy Studies-2. The pooled sensitivity, specificity, diagnostic odds ratio (DOR), and area under receiver operating characteristic curve of ADC values were calculated to determine the diagnostic performance. Seven studies with a total of 236 patients were included. The pooled sensitivity, specificity, DOR, and area under curve were 93% (95% CI 77%-98%), 85% (95% CI 72%-93%), 78 (95% CI 15-401), and 0.91 (95% CI 0.89-0.94), respectively, for the ▵ADC; and 75% (95% CI 62%-84%), 90% (95% CI 67%-97%), 26 (95% CI 6-110), and 0.85 (95% CI 0.82-0.88), respectively, for the post-ADC. For pre-ADC, meta-analysis was not performed because of conflicting results. In conclusions, our results demonstrate that DW-MRI has good performance for evaluating the response to chemoradiation therapy in patients with esophageal cancer. ▵ADC and post-ADC are promising reliable and valuable predictors.

The Chinese Society of Clinical Oncology (CSCO): clinical guidelines for the diagnosis and treatment of gastric cancer

China is one of the countries with the highest incidence of gastric cancer. There are differences in epidemiological characteristics, clinicopathological features, tumor biological characteristics, treatment patterns, and drug selection between gastric cancer patients from the Eastern and Western countries. Non-Chinese guidelines cannot specifically reflect the diagnosis and treatment characteristics for the Chinese gastric cancer patients. The Chinese Society of Clinical Oncology (CSCO) arranged for a panel of senior experts specializing in all sub-specialties of gastric cancer to compile, discuss, and revise the guidelines on the diagnosis and treatment of gastric cancer based on the findings of evidence-based medicine in China and abroad. By referring to the opinions of industry experts, taking into account of regional differences, giving full consideration to the accessibility of diagnosis and treatment resources, these experts have conducted experts’ consensus judgement on relevant evidence and made various grades of recommendations for the clinical diagnosis and treatment of gastric cancer to reflect the value of cancer treatment and meeting health economic indexes. This guideline uses tables and is complemented by explanatory and descriptive notes covering the diagnosis, comprehensive treatment, and follow-up visits for gastric cancer.

Imaging strategies in the management of gastric cancer: current role and future potential of MRI

Accurate preoperative staging of gastric cancer and the assessment of tumor response to neoadjuvant treatment is of importance for treatment and prognosis. Current imaging techniques, mainly endoscopic ultrasonography (EUS), computed tomography (CT) and ¹⁸F-fluorodeoxyglucose positron emission tomography (¹⁸F-FDG PET), have their limitations. Historically, the role of magnetic resonance imaging (MRI) in gastric cancer has been limited, but with the continuous technical improvements, MRI has become a more potent imaging technique for gastrointestinal malignancies. The accuracy of MRI for T- and N-staging of gastric cancer is similar to EUS and CT, making MRI a suitable alternative to other imaging strategies. There is limited evidence on the performance of MRI for M-staging of gastric cancer specifically, but MRI is widely used for diagnosing liver metastases and shows potential for diagnosing peritoneal seeding. Recent pilot studies showed that treatment response assessment as well as detection of lymph node metastases and systemic disease might benefit from functional MRI (e.g. diffusion weighted imaging and dynamic contrast enhancement). Regarding treatment guidance, additional value of MRI might be expected from its role in better defining clinical target volumes and setup verification with MR-guided radiation treatment.

Early response evaluation of neoadjuvant therapy with PET/MRI to predict resectability in patients with adenocarcinoma of the esophagogastric junction

STUDY DESIGN AND PURPOSE

Positron emission tomography (PET)/magnetic resonance imaging (MRI) is a new modality that has showed promising results for various clinical indications. Currently, evaluation of neoadjuvant therapy (NT) among patients with adenocarcinoma of the esophagogastric junction has primarily been reserved for PET/computed tomography. Our aim was to evaluate if early response evaluation by PET/MRI is a feasible method to predict resectability.

METHODS AND MATERIALS

Patients with untreated adenocarcinoma of the esophagogastric junction (Siewert types I/II) and fit for NT with no contraindications for PET/MRI were considered eligible. A baseline scan was performed prior to NT induction and an evaluation scan 3 weeks later. For histopathological response evaluation, the Mandard tumor regression grade score was applied. Response on PET/MRI was evaluated with Response Evaluation Criteria in Solid Tumors (RECIST 1.1), and change in ADC and SUV_max values.

RESULTS

Twenty-eight patients were enrolled, and 22 completed both scans and proceeded to final analyses. Seventeen patients were found resectable versus five who were found unresectable. PET/MRI response evaluation had a sensitivity 94%, specificity 80%, and AUC = 0.95 when predicting resectability in patients with adenocarcinoma of the esophagogastric junction. No association with histopathological response (tumor regression grade) was found nor was RECIST correlated with resectability.

CONCLUSION

Response evaluation using PET/MRI was a feasible method to predict resectability in patients with adenocarcinoma of the esophagogastric junction in this pilot study. However, larger studies are warranted to justify the use of the modality for this indication.

Value of multi-slice spiral computed tomography in the diagnosis of metastatic lymph nodes and N-stage of gastric cancer

Objective

To establish new diagnostic criteria for improvement of the accuracy of multi-slice spiral computed tomography (MSCT) in diagnosing the N-stage and lymph node (LN) metastasis of gastric cancer (GC).

Methods

MSCT was performed with plain and triphasic dynamic contrast enhancement. Different regions of LN metastasis and N-staging were determined according to the herein-proposed combined diagnostic criteria and were then correlated with the pathological analysis. The Kappa consistency test was used to study the accuracy of MSCT.

Results

The accuracy of MSCT in diagnosing the N-stage as a whole was 86.3%, and that in diagnosing LN metastasis was 79.1% to 98.9%. The Kappa values for stages N0, N1, and N3 ranged from 0.449 to 0.662, indicating good consistency in diagnosing these three stages between MSCT and the postsurgical pathological results. The K_total value was 0.567 between MSCT and the postsurgical pathological results in diagnosing LN metastasis. The risk of LN metastasis increased with the progression of lesion infiltrates.

Conclusions

Application of the combined diagnostic criteria increased the diagnostic performance of MSCT in not only judging the N-stage but also diagnosing LN metastasis. This study will provide valuable reference data for surgical planning for patients with GC in the clinical setting.

Diffusion MRI of cancer: From low to high b-values

Following its success in early detection of cerebral ischemia, diffusion-weighted imaging (DWI) has been increasingly used in cancer diagnosis and treatment evaluation. These applications are propelled by the rapid development of novel diffusion models to extract biologically valuable information from diffusion-weighted MR signals, and significant advances in MR hardware that has enabled image acquisition with high b-values. This article reviews recent technical developments and clinical applications in cancer imaging using DWI, with a special emphasis on high b-value diffusion models. The article is organized in four sections. First, we provide an overview of diffusion models that are relevant to cancer imaging. The model parameters are discussed in relation to three tissue properties-cellularity, vascularity, and microstructures. An emphasis is placed on characterization of microstructural heterogeneity, given its novelty and close relevance to cancer. Second, we illustrate diffusion MR clinical applications in each of the following three categories: 1) cancer detection and diagnosis; 2) cancer grading, staging, and classification; and 3) cancer treatment response prediction and evaluation. Third, we discuss several practical issues, including selection of image acquisition parameters, reproducibility and reliability, motion management, image distortion, etc., that are commonly encountered when applying DWI to cancer in clinical settings. Lastly, we highlight a few ongoing challenges and provide some possible future directions, particularly in the area of establishing standards via well-organized multicenter clinical trials to accelerate clinical translation of advanced DWI techniques to improving cancer care on a large scale. Level of Evidence: 5 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:23-40.

Gastric cancer and imaging biomarkers: Part 1 - a critical review of DW-MRI and CE-MDCT findings

Abstract

The current standard of care for gastric cancer imaging includes heterogeneity in image acquisition techniques and qualitative image interpretation. In addition to qualitative assessment, several imaging techniques, including diffusion-weighted magnetic resonance imaging (DW-MRI), contrast-enhanced multidetector computed tomography (CE-MDCT), dynamic-contrast enhanced MRI and 18F-fluorodeoxyglucose positron emission tomography, can allow quantitative analysis. However, so far there is no consensus regarding the application of functional imaging in the management of gastric cancer. The aim of this article is to specifically review two promising biomarkers for gastric cancer with reasonable spatial resolution: the apparent diffusion coefficient (ADC) from DW-MRI and textural features from CE-MDCT. We searched MEDLINE/ PubMed for manuscripts published from inception to 6 February 2018. Initially, we searched for (gastric cancer OR gastric tumour) AND diffusion weighted magnetic resonance imaging. Then, we searched for (gastric cancer OR gastric tumour) AND texture analysis AND computed tomography. We collated the results from the studies related to this query. There is evidence that: (1) the ADC is a promising biomarker for the evaluation of the aggressiveness (T and N stage), treatment response and prognosis of gastric cancer; (2) textural features are related to the degree of differentiation, Lauren classification, treatment response and prognosis of gastric cancer. We conclude that these imaging biomarkers hold promise as effective additional tools in the diagnostic pathway of gastric cancer and may facilitate the multidisciplinary work between the radiologist and clinician, and across different institutions, to provide a greater biological understanding of gastric cancer.

Key Points

• Quantitative imaging is the extraction of quantifiable features from medical images for the assessment of normal or pathological conditions and represents a promising area for gastric cancer.

• Quantitative analysis from CE-MDCT and DW-MRI allows the extrapolation of multiple imaging biomarkers.

• ADC from DW-MRI and CE- MDCT-based texture features are non-invasive, quantitative imaging biomarkers that hold promise in the evaluation of the aggressiveness, treatment response and prognosis of gastric cancer.

Locally advanced gastric cancer: total iodine uptake to predict the response of primary lesion to neoadjuvant chemotherapy

PURPOSE

Pathologic response to neoadjuvant chemotherapy is a prognostic factor in many cancer types. However, the existing evaluative criteria are deficient. We sought to prospectively evaluate the total iodine uptake derived from dual-energy computed tomography (DECT) in predicting treatment efficacy and progression-free survival (PFS) time in gastric cancer after neoadjuvant chemotherapy.

METHODS

From October 2012 to December 2015, 44 patients with locally advanced gastric cancer were examined with DECT 1 week before and three cycles after neoadjuvant chemotherapy. The percentage changes in tumor area (%ΔS), diameter (%ΔD), and density (%ΔHU) were calculated to evaluate the WHO, RESCIST, and Choi criteria. The percentage changes in tumor volume (%ΔV) and total iodine uptake of portal phase (%ΔTIU-p) were also calculated to determine cut-off values by ROC curves. The correlation between the different criteria and histopathologic tumor regression grade (Becker score) or PFS were statistically analyzed.

RESULTS

Forty-four patients were divided into responders and non-responders according to 43.34% volume reduction (P = 0.002) and 63.87% (P = 0.002) TIU-p reduction, respectively. The %ΔTIU-p showed strong (r = 0.602, P = 0.000) and %ΔV showed moderate (r = 0.416, P = 0.005), while the WHO (r = 0.075, P = 0.627), RECIST (r = 0.270, P = 0.077) and Choi criteria (r = 0.238, P = 0.120) showed no correlation with the Becker score. The differences in PFS time between the responder and non-responder groups were significant according to %ΔTIU-p and Choi criteria (P = 0.001 and P = 0.013, respectively).

CONCLUSIONS

The TIU-p can help predict pathological regression in advanced gastric cancer patients after neoadjuvant chemotherapy. In addition, the %ΔTIU-p could be one of the potentially valuable predictive parameters of the PFS time.

Radiomic analysis using contrast-enhanced CT: predict treatment response to pulsed low dose rate radiotherapy in gastric carcinoma with abdominal cavity metastasis

Background

To determine the feasibility of radiomic analysis for predicting the therapeutic response of gastric carcinoma (GC) with abdominal cavity metastasis (GCACM) to pulsed low dose rate radiotherapy (PLDRT) using contrast-enhanced computed tomography (CECT) images.

Methods

Pretreatment CECT images of 43 GCACM patients were analyzed. Patients with complete response (CR) and partial response (PR) were considered responders, while stable disease (SD) and progressive disease (PD) as non-responders. A total of 1,117 image features were quantified from tumor region that segmented from arterial phase CT images. Intra-class correlation coefficient (ICC) and absolute correlation coefficient (ACC) were calculated for selecting influential feature subset. The capability of each influential feature on treatment response classification was assessed using Kruskal-Wallis test and receiver operating characteristic (ROC) analysis. Moreover, artificial neural network (ANN) and k-nearest neighbor (KNN) predictive models were constructed based on the training set (18 responders, 14 non-responders) and the testing set (6 responders, 5 non-responders) validated the reliability of the models. Comparison between the performances of the models was performed by using McNemar's test.

Results

The analyses showed that 6 features (1 first order-based, 1 texture-based, 1 LoG-based, and 3 wavelet-based) were significantly different between responders and non-responders (AUCs range from 0.686 to 0.728). Both two prediction models based on features extracted from CECT showed potential in predicting the treatment response with higher accuracies (ANN: 0.714, KNN: 0.749 for the training set; ANN: 0.816, KNN: 0.816 for the testing set). No statistical difference was observed between the performance of ANN and KNN (P=0.999).

Conclusions

Pretreatment radiomic analysis using CECT can potentially provide important information regarding the therapeutic response to PLDRT for GCACM, improving risk stratification.

Comparison of DWI and 18F-FDG PET/CT for assessing preoperative N-staging in gastric cancer: evidence from a meta-analysis

The diagnostic values of diffusion weighted imaging (DWI) and ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) for N-staging of gastric cancer (GC) were identified and compared. After a systematic search to identify relevant articles, meta-analysis was used to summarize the sensitivities, specificities, and areas under curves (AUCs) for DWI and PET/CT. To better understand the diagnostic utility of DWI and PET/CT for N-staging, the performance of multi-detector computed tomography (MDCT) was used as a reference. Fifteen studies were analyzed. The pooled sensitivity, specificity, and AUC with 95% confidence intervals of DWI were 0.79 (0.73–0.85), 0.69 (0.61–0.77), and 0.81 (0.77–0.84), respectively. For PET/CT, the corresponding values were 0.52 (0.39–0.64), 0.88 (0.61–0.97), and 0.66 (0.62–0.70), respectively. Comparison of the two techniques revealed DWI had higher sensitivity and AUC, but no difference in specificity. DWI exhibited higher sensitivity but lower specificity than MDCT, and ¹⁸F-FDG PET/CT had lower sensitivity and equivalent specificity. Overall, DWI performed better than ¹⁸F-FDG PET/CT for preoperative N-staging in GC. When the efficacy of MDCT was taken as a reference, DWI represented a complementary imaging technique, while ¹⁸F-FDG PET/CT had limited utility for preoperative N-staging.

Biomarkers from in vivo molecular imaging of breast cancer: pretreatment 18F-FDG PET predicts patient prognosis, and pretreatment DWI-MR predicts response to neoadjuvant chemotherapy

OBJECTIVE

Human cancers display intra-tumor phenotypic heterogeneity and recent research has focused on developing image processing methods extracting imaging descriptors to characterize this heterogeneity. This work assesses the role of pretreatment 18F-FDG PET and DWI-MR with respect to the prognosis and prediction of neoadjuvant chemotherapy (NAC) outcomes when image features are used to characterize primitive lesions from breast cancer (BC).

MATERIALS AND METHODS

A retrospective protocol included 38 adult women with biopsy-proven BC. Patients underwent a pre-therapy 18F-FDG PET/CT whole-body study and a pre-therapy breast multi-parametric MR study. Patients were then referred for NAC treatment and then for surgical resection, with an evaluation of the therapy response. Segmentation methods were developed in order to identify functional volumes both on 18F-FDG PET images and ADC maps. Macroscopic and histogram features were extracted from the defined functional volumes.

RESULTS

Our work demonstrates that macroscopic and histogram features from 18F-FDG PET are able to biologically characterize primitive BC, and define the prognosis. In addition, histogram features from ADC maps are able to predict the response to NAC.

CONCLUSION

Our work suggests that pre-treatment 18F-FDG PET and pre-treatment DWI-MR provide useful complementary information for biological characterization and NAC response prediction in BC.

Pre-treatment MDCT-based texture analysis for therapy response prediction in gastric cancer: Comparison with tumour regression grade at final histology

PURPOSE

An accurate prediction of tumour response to therapy is fundamental in oncology, so as to prompt personalised treatment options if needed. The aim of this study was to investigate the ability of preoperative texture analysis from multi-detector computed tomography (MDCT) in the prediction of the response rate to neo-adjuvant therapy in patients with gastric cancer.

MATERIAL AND METHODS

Thirty-four patients with biopsy-proven gastric cancer were examined by MDCT before neo-adjuvant therapy, and treated with radical surgery after treatment completion. Tumour regression grade (TRG) at final histology was also assessed. Image features from texture analysis were quantified, with and without filters for fine to coarse textures. Patients with TRG 1-3 were considered responders while TRG 4-5 as non- responders. The response rate to neo-adjuvant therapy was assessed both at univariate and multivariate analysis.

RESULTS

Fourteen parameters were significantly different between the two subgroups at univariate analysis; in particular, entropy and compactness (higher in responders) and uniformity (lower in responders). According to our model, the following parameters could identify non-responders at multivariate analysis: entropy (≤6.86 with a logarithm of Odds Ratio - Log OR -: 4.11; p=0.003); range (>158.72; Log OR: 3.67; p=0.010) and root mean square (≤3.71; Log OR: 4.57; p=0.005). Entropy and three-dimensional volume were not significantly correlated (r=0.06; p=0.735).

CONCLUSION

Pre-treatment texture analysis can potentially provide important information regarding the response rate to neo-adjuvant therapy for gastric cancer, improving risk stratification.

Meta-Analysis of the Correlation between Apparent Diffusion Coefficient and Standardized Uptake Value in Malignant Disease

The objective of this meta-analysis is to explore the correlation between the apparent diffusion coefficient (ADC) on diffusion-weighted MR and the standard uptake value (SUV) of ¹⁸F-FDG on PET/CT in patients with cancer. Databases such as PubMed (MEDLINE included), EMBASE, and Cochrane Database of Systematic Review were searched for relevant original articles that explored the correlation between SUV and ADC in English. After applying Fisher's r-to-z transformation, correlation coefficient (r) values were extracted from each study and 95% confidence intervals (CIs) were calculated. Sensitivity and subgroup analyses based on tumor type were performed to investigate the potential heterogeneity. Forty-nine studies were eligible for the meta-analysis, comprising 1927 patients. Pooled r for all studies was −0.35 (95% CI: −0.42–0.28) and exhibited a notable heterogeneity (I² = 78.4%; P < 0.01). In terms of the cancer type subgroup analysis, combined correlation coefficients of ADC/SUV range from −0.12 (lymphoma, n = 5) to −0.59 (pancreatic cancer, n = 2). We concluded that there is an average negative correlation between ADC and SUV in patients with cancer. Higher correlations were found in the brain tumor, cervix carcinoma, and pancreas cancer. However, a larger, prospective study is warranted to validate these findings in different cancer types.

Contribution of diffusion weighted MRI to diagnosis and staging in gastric tumors and comparison with multi-detector computed tomography

Background

Diagnostic performance of Diffusion-Weighted magnetic resonance Imaging (DWI) and Multi-Detector Computed Tomography (MDCT) for TNM (Tumor, Lymph node, Metastasis) staging of gastric cancer was compared.

Patients and methods

We used axial T2-weighted images and DWI (b-0,400 and b-800 s/mm2) protocol on 51 pre-operative patients who had been diagnosed with gastric cancer. We also conducted MDCT examinations on them. We looked for a signal increase in the series of DWI images. The depth of tumor invasion in the stomach wall (tumor (T) staging), the involvement of lymph nodes (nodal (N) staging), and the presence or absence of metastases (metastatic staging) in DWI and CT images according to the TNM staging system were evaluated. In each diagnosis of the tumors, sensitivity, specificity, positive and negative accuracy rates of DWI and MDCT examinations were found through a comparison with the results of the surgical pathology, which is the gold standard method. In addition to the compatibilities of each examination with surgical pathology, kappa statistics were used.

Results

Sensitivity and specificity of DWI and MDCT in lymph node staging were as follows: N1: DWI: 75.0%, 84.6%; MDCT: 66.7%, 82%;N2: DWI: 79.3%, 77.3%; MDCT: 69.0%, 68.2%; N3: DWI: 60.0%, 97.6%; MDCT: 50.0%, 90.2%. The diagnostic tool DWI seemed more compatible with the gold standard method (surgical pathology), especially in the staging of lymph node, when compared to MDCT. On the other hand, in T staging, the results of DWI and MDCT were better than the gold standard when the T stage increased. However, DWI did not demonstrate superiority to MDCT. The sensitivity and specificity of both imaging techniques for detecting distant metastasis were 100%.

Conclusions

The diagnostic accuracy of DWI for TNM staging in gastric cancer before surgery is at a comparable level with MDCT and adding DWI to routine protocol of evaluating lymph nodes metastasis might increase diagnostic accuracy.

The value of FDG-PET in the staging of gastric adenocarcinoma: A single institution retrospective review

BACKGROUND

The value of FDG-PET in the staging of gastric adenocarcinoma (GA) has been subject to debate.

METHODS

We performed a retrospective review of GA patients between 2006 and 2014 and identified those who had a CT and FDG-PET before initiating treatment. CT and FDG-PET images were analyzed by a blinded body radiologist and nuclear physician, respectively. Disease stage was assessed, looking at primary tumor (PT), locoregional (LLN) and distant lymph node disease (DLN), and metastasis (M).

RESULTS

We identified 608 patients who had biopsy-proven GA and 207 (34.0%) had a CT and FDG-PET as part of their staging work-up. Of these, imaging from 166 (27.3%) patients was available for review. CT identified PT, LLN, DLN, and M in 120 (72.3%), 84 (50.6%), 25 (15.1%), and 32 (19.3%) patients, respectively; while FDG-PET identified PT, LLN, DLN, and M in 125 (75.3%), 78 (47.0%), 41 (24.7%), and 27 (16.3%) of patients, respectively. FDG-PET up-staged 31 (18.7%) patients while it down-staged 17 (10.2%) patients. Of patients who were up-staged, 20 (64.5%) developed progressive disease.

CONCLUSIONS

Our findings support the use of FDG-PET as a valuable adjunct to CT in the staging of GA, as it changed the stage in 48 (28.9%) patients. J. Surg. Oncol. 2016;113:640-646. © 2016 Wiley Periodicals, Inc.

Apparent diffusion coefficient by diffusion-weighted magnetic resonance imaging as a sole biomarker for staging and prognosis of gastric cancer

Objective

To investigate the role of apparent diffusion coefficient (ADC) from diffusion-weighted magnetic resonance imaging (DW-MRI) when applied to the 7th TNM classification in the staging and prognosis of gastric cancer (GC).

Methods

Between October 2009 and May 2014, a total of 89 patients with non-metastatic, biopsy proven GC underwent 1.5T DW-MRI, and then treated with radical surgery. Tumor ADC was measured retrospectively and compared with final histology following the 7th TNM staging (local invasion, nodal involvement and according to the different groups — stage I, II and III). Kaplan-Meier curves were also generated. The follow-up period is updated to May 2016.

Results

Median follow-up period was 33 months and 45/89 (51%) deaths from GC were observed. ADC was significantly different both for local invasion and nodal involvement (P<0.001). Considering final histology as the reference standard, a preoperative ADC cut-off of 1.80×10^–3 mm²/s could distinguish between stages I and II and an ADC value of ≤1.36×10^–3 mm²/s was associated with stage III (P<0.001). Kaplan-Meier curves demonstrated that the survival rates for the three prognostic groups were significantly different according to final histology and ADC cut-offs (P<0.001).

Conclusions

ADC is different according to local invasion, nodal involvement and the 7th TNM stage groups for GC, representing a potential, additional prognostic biomarker. The addition of DW-MRI could aid in the staging and risk stratification of GC.

Clinical Utility of Positron Emission Tomography Magnetic Resonance Imaging (PET-MRI) in Gastrointestinal Cancers

Anatomic imaging utilizing both CT (computed tomography) and MRI (magnetic resonance imaging) limits the assessment of cancer metastases in lymph nodes and distant organs while functional imaging like PET (positron emission tomography) scan has its limitation in spatial resolution capacity. Hybrid imaging utilizing PET-CT and PET-MRI are novel imaging modalities that are changing the current landscape in cancer diagnosis, staging, and treatment response. MRI has shown to have higher sensitivity in soft tissue, head and neck pathology, and pelvic disease, as well as, detecting small metastases in the liver and bone compared to CT. Combining MRI with PET allows for detection of metastases that may have been missed with current imaging modalities. In this review, we will examine the clinical utility of FDG PET-MRI in the diagnosis and staging of gastrointestinal cancers with focus on esophageal, stomach, colorectal, and pancreatic cancers. We will also explore its role in treatment response and future directions associated with it.

Gastric cancer: texture analysis from multidetector computed tomography as a potential preoperative prognostic biomarker

OBJECTIVES

To investigate the association between preoperative texture analysis from multidetector computed tomography (MDCT) and overall survival in patients with gastric cancer.

METHODS

Institutional review board approval and informed consent were obtained. Fifty-six patients with biopsy-proved gastric cancer were examined by MDCT and treated with surgery. Image features from texture analysis were quantified, with and without filters for fine to coarse textures. The association with survival time was assessed using Kaplan-Meier and Cox analysis.

RESULTS

The following parameters were significantly associated with a negative prognosis, according to different thresholds: energy [no filter] - Logarithm of relative risk (Log RR): 3.25; p = 0.046; entropy [no filter] (Log RR: 5.96; p = 0.002); entropy [filter 1.5] (Log RR: 3.54; p = 0.027); maximum Hounsfield unit value [filter 1.5] (Log RR: 3.44; p = 0.027); skewness [filter 2] (Log RR: 5.83; p = 0.004); root mean square [filter 1] (Log RR: - 2.66; p = 0.024) and mean absolute deviation [filter 2] (Log RR: - 4.22; p = 0.007).

CONCLUSIONS

Texture analysis could increase the performance of a multivariate prognostic model for risk stratification in gastric cancer. Further evaluations are warranted to clarify the clinical role of texture analysis from MDCT.

KEY POINTS

• Textural analysis from computed tomography can be applied in gastric cancer. • Preoperative non-invasive texture features are related to prognosis in gastric cancer. • Texture analysis could help to evaluate the aggressiveness of this tumour.

Advances in imaging of gastric cancer

Due to the advances in imaging technology, the diagnosis, staging, and efficacy evaluation of gastric cancer by imaging are continuously improving. This paper comprehensively analyzes different imaging methods in cancer research, focusing on new imaging techniques for the diagnosis and treatment of gastric cancer, their advantages and limitations in clinical application, and the opportunities and challenges. Radiologists can take the initiative to collaborate with relevant clinical departments through a multidisciplinary platform with an open mind in the face of various problems presented clinically, understand the requirements for standardized diagnosis and treatment of gastric cancer, and fully communicate with imaging equipment providers and engineering and technical personnel to explore more methods and indicators to improve the diagnosis of this malignancy.

DWI as a Quantitative Biomarker in Predicting Chemotherapeutic Efficacy at Multitime Points on Gastric Cancer Lymph Nodes Metastases

The purpose of the hypothesis testing is to determine that apparent diffusion coefficient (ADC) as an early biomarker can predict the metastatic lymph nodes' (LNs) response to neoadjuvant chemotherapy in advanced gastric cancer (GC) in early stage. From March 2011 to June 2015, 106 patients with advanced GC were enrolled in the study. Patients underwent conventional magnetic resonance imaging and functional diffusion weighted imaging before and 3 days, 7 days, 30 days, and 60 days following the standard chemotherapy. After surgery, among 3034 detected LNs, the positive group was divided into complete response (CR) group, partial response (PR) group, and stable disease (SD) group in accordance to the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. Mean ADCs, short/long diameters of LNs before chemotherapy between the whole positive and the negative LNs were compared by t test. Changes of mean ADCs in 3 groups were analyzed by 1-way ANOVA. The mean ADC of the whole positive LNs was (1.145 ± 0.014) × 10⁻³ mm²/s, which was significantly lower than that of the whole negative LNs ([1.491 ± 0.010] × 10⁻³ mm²/s; P < 0.05). The means of both short/long diameters in the whole positive LNs were significantly longer than those in the whole negative LNs (P < 0.05). In CR, PR, and SD groups, the mean ADC of metastatic LNs on the 3rd day, 7th day, 13th day, and 16th day following the chemotherapy were all higher than that of LNs before chemotherapy, respectively (all P < 0.05). In addition, significant difference was found between mean ADCs in any 2 time points (all P < 0.05), except between mean ADCs in the 3rd day and in the 7th day of the chemotherapy. In conclusion, ADC can be used as an early biomarker to predict the metastatic LNs' response to neoadjuvant chemotherapy in advanced GC in early stage.

Diagnostic accuracy of diffusion-weighted magnetic resonance imaging versus positron emission tomography/computed tomography for early response assessment of liver metastases to Y90-radioembolization

Objectives

Patients with hepatic metastases who are candidates for Y90-radioembolization (Y90-RE) usually have advanced tumor stages with involvement of both liver lobes. Per current guidelines, these patients have usually undergone several cycles of potentially hepatotoxic systemic chemotherapy before Y90-RE is at all considered, requiring split (lobar) treatment sessions to reduce hepatic toxicity. Assessing response to Y90-RE early, that is, already after the first lobar session, would be helpful to avoid an ineffective and potentially hepatotoxic second lobar treatment. We investigated the accuracy with which diffusion- weighted magnetic resonance imaging (DWI-MRI) and positron emission tomography/computed tomography (PET/CT) can provide this information.

Methods

An institutional review board–approved prospective intraindividual comparison trial on 35 patients who underwent fluorodeoxyglucose PET/CT and DWI-MRI within 6 weeks before and 6 weeks after Y90-RE to treat secondary-progressive liver metastases from solid cancers (20 colorectal, 13 breast, 2 other) was performed. An increase of minimal apparent diffusion coefficient (ADCmin) or decrease of maximum standard uptake value (SUVmax) by at least 30% was regarded as positive response. Long-term clinical and imaging follow-up was used to distinguish true- from false-response classifications.

Results

On the basis of long-term follow-up, 23 (66%) of 35 patients responded to the Y90 treatment. No significant changes of metastases size or contrast enhancement were observable on pretreatment versus posttreatment CT or magnetic resonance images.However, overall SUVmax decreased from 8.0 ± 3.9 to 5.5 ± 2.2 (P < 0.0001), and ADCmin increased from 0.53 ± 0.13 × 10⁻³ mm²/s to 0.77 ± 0.26 × 10⁻³ mm²/s (P < 0.0001). Pretherapeutic versus posttherapeutic changes of ADCmin and SUVmax correlated moderately (r = −0.53). In 4 of the 35 patients (11%), metastases were fluorodeoxyglucose-negative such that no response assessment was possible by PET. In 25 (71%) of the 35 patients, response classification by PET and DWI-MRI was concordant; in 6 (17%) of the 35, it was discordant. In 5 of the 6 patients with discordant classifications, follow-up confirmed diagnoses made by DWI. The positive predictive value to predict response was 22 (96%) of 23 for MRI and 15 (88%) of 17 for PET. The negative predictive value to predict absence was 11 (92%) of 12 for MRI and 10 (56%) of 18 for PET. Sensitivity for detecting response was significantly higher for MRI (96%; 22/23) than for PET (65%; 15/23) (P < 0.02).

Conclusions

Diffusion-weighted magnetic resonance imaging appears superior to PET/CT for early response assessment in patients with hepatic metastases of common solid tumors. It may be used in between lobar treatment sessions to guide further management of patients who undergo Y90-RE for hepatic metastases.

Preoperative locoregional staging of gastric cancer: is there a place for magnetic resonance imaging? Prospective comparison with EUS and multidetector computed tomography

BACKGROUND

The aim of this study was to prospectively compare the diagnostic performance of magnetic resonance imaging (MRI), multidetector computed tomography (MDCT) and endoscopic ultrasonography (EUS) in the preoperative locoregional staging of gastric cancer.

METHODS

This study had Institutional Review Board approval, and informed consent was obtained from all patients. Fifty-two patients with biopsy-proven gastric cancer underwent preoperative 1.5-T MRI, 64-channel MDCT and EUS. All images were analysed blind, and the results were compared with histopathological findings according to the seventh edition of the TNM classification. After the population had been divided on the basis of the local invasion (T1-3 vs T4a-b) and nodal involvement (N0 vs N+), sensitivity, specificity, positive and negative predictive value, and accuracy were calculated and diagnostic performance measures were assessed using the McNemar test.

RESULTS

For T staging, EUS showed higher sensitivity (94%) than MDCT and MRI (65 and 76%; p = 0.02 and p = 0.08). MDCT and MRI had significantly higher specificity (91 and 89%) than EUS (60%) (p = 0.0009 and p = 0.003). Adding MRI to MDCT or EUS did not result in significant differences for sensitivity. For N staging, EUS showed higher sensitivity (92%) than MRI and MDCT (69 and 73%; p = 0.01 and p = 0.02). MDCT showed better specificity (81%) than EUS and MRI (58 and 73%; p = 0.03 and p = 0.15).

CONCLUSIONS

Our prospective study confirmed the leading role of EUS and MDCT in the staging of gastric cancer and did not prove, at present, the value of the clinical use of MRI.

Correlation between apparent diffusion coefficients and HER2 status in gastric cancers: pilot study

Background

To evaluate whether apparent diffusion coefficient (ADC) value of gastric cancer obtained from diffusion weighted imaging (DWI) correlates with the HER2 status.

Methods

Forty-five patients, who had been diagnosed with gastric cancer through biopsy, were enrolled in this IRB-approved study. Each patient underwent a DWI (b values: 0 and 1,000 sec/mm²) prior to surgery (curative gastrectomy or palliative resection). Postoperative microscopic findings, HER2 status by immunohistochemical analysis and fluorescence in situ hybridization (FISH) were obtained. HER2 status was compared among gastric cancers with various histopathological features using the chi square test. The ADC values of gastric cancers with positive and negative HER2 were compared using the student t test.

Results

A weak yet significant correlation was observed between the mean ADC values and HER2 status (r = 0.312, P = 0.037) and scores (r = 0.419, P = 0.004). The mean ADC value of HER2-positive gastric cancers was significantly higher than those of HER2-negative tumors (1.211 vs. 0.984 mm²/s, P = 0.020). The minimal ADC value of HER2-positive gastric cancers was significantly higher than those of HER2-negative tumors (1.105 vs. 0.905 × 10⁻³ mm²/s, P = 0.036).

Conclusions

In this pilot study, we have demonstrated that the ADC values of gastric cancer correlate with the HER2 status. Future research is warranted to see if DWI can predict HER2 status and help in tailoring therapy for gastric cancer.

Prognostic utility of diffusion-weighted MRI in oesophageal cancer: is apparent diffusion coefficient a potential marker of tumour aggressiveness?

PURPOSE

To investigate the role of the apparent diffusion coefficient (ADC) as a potential prognostic biomarker in the evaluation of the aggressiveness of oesophageal cancer.

MATERIALS AND METHODS

Between November 2009 and December 2013, 43 patients with evidence of oesophageal or oesophago-gastric junction cancer were referred to our institution and prospectively entered in our database. The final study population consisted of 23 patients (18 men; 5 women; mean age, 64.62 ± 10.91 years) who underwent diffusion-weighted Magnetic Resonance before surgical intervention. Specifically, 14 were directly treated with surgery and 9 were addressed to chemo/radiotherapy beforehand. Two radiologists independently measured mean tumour ADC and inter-observer agreement (Spearman's and intraclass correlation coefficient [ICC]) was assessed. In the univariate analysis, overall survival curves related to pathological ADC, pT, pN, tumour location and histotype were fitted using the Kaplan-Meier method. Survival curves were then compared using the log-rank test.

RESULTS

Inter-observer reproducibility was very good (Spearman's rho = 0.95; ICC = 0.94). At a total median follow-up of 19 months (2-49 months), 4 patients had died. The median follow-up was 18.50 months (5-49 months) for the surgery-only group (1/4 events, 25 %) and 24 months (2-34 months) for the chemo/radiotherapy group (3/4 events, 75 %). Survival time at 48 months for the overall population was 59 % (±0.11), while for the surgery-only group and the chemo/radiotherapy group was 90 % (±0.09) and 61 % (±0.34), respectively. In the univariate analysis, ADC values below or equal to 1.4 × 10(-3) mm(2)/s were associated with a negative prognosis both in the total population (P = 0.016) and in the surgery-only group (P < 0.001).

CONCLUSION

Despite the biggest limitation of our study (i.e. the small study population), we were able to show that pathological ADC could be considered a prognostic factor for oesophageal cancer. DWI might be introduced into clinical practice as a promising and reliable technique in the diagnostic pathway of this tumour.

Prognostic Role of Diffusion-weighted MR Imaging for Resectable Gastric Cancer

PURPOSE

To prospectively investigate the role of apparent diffusion coefficient (ADC) calculated from diffusion-weighted magnetic resonance (MR) imaging as a potential prognostic biomarker in the evaluation of the aggressiveness of gastric cancer.

MATERIALS AND METHODS

This prospective study had institutional review board approval. Informed consent was obtained from all patients. Between October 2009 and December 2013, a total of 99 patients (65 men, 34 women; mean age, 62.02 years; age range, 32.33-85.15 years) with biopsy-proved cancer (28 esophagogastric junction and 71 gastric cancers) were examined with a 1.5-T MR imaging system, including T1-, T2-, and diffusion-weighted sequences. ADC measurements were obtained. Seventy-one patients were directly treated with surgery, while 28 underwent neoadjuvant chemotherapy beforehand. Pathologic ADC, pathologic T and N stages, tumor location, surgical approach, and histologic subtype were investigated with univariate and multivariate analyses by using the Cox regression model.

RESULTS

At a total median follow-up period of 21 months, 31 patients had died. The median follow-up was 25 months for the surgery-only group (19 of 31 events [61%]) and 28 months for the chemotherapy group (12 of 31 events [39%]). In the multivariate analysis, ADC values of 1.5 × 10(-3) mm(2)/sec or lower were associated with a negative prognosis, both in the total population (log-relative risk, 1.73; standard error, 0.56; P = .002) and in the surgery-only (log-relative risk, 1.97; standard error, 0.66; P = .003) and chemotherapy (log-relative risk, 2.93; standard error, 1.41; P = .03) groups, along with other significant prognostic factors (in particular, pathologic T and N stages).

CONCLUSION

Pathologic ADC represents a strong independent prognostic factor in the evaluation of the aggressiveness of gastric cancer, in addition to clinical and surgical variables.

Towards personalized perioperative treatment for advanced gastric cancer

Gastric cancer is one of the most frequently diagnosed cancers worldwide. Although the rate of gastric cancer has declined dramatically over the past decades in most developed Western countries, it has not declined in East Asia. Currently, a radical gastrectomy is still the only curative treatment for gastric cancer. Over the last twenty years, however, surgery alone has been replaced by a multimodal perioperative approach. To achieve the maximum benefit from the perioperative treatment, a thorough evaluation of the tumor must first be performed. A complete assessment of gastric cancer is divided into two parts: staging and histology. According to the stage and histology of the cancer, perioperative chemotherapy or radiochemotherapy can be implemented, and perioperative targeted therapies such as trastuzumab may also play a role in this field. However, perioperative treatment approaches have not been widely accepted until a series of clinical trials were performed to evaluate the value of perioperative treatment. Although multimodal perioperative treatment has been widely applied in clinical practice, personalization of perioperative treatment represents the next stage in the treatment of gastric cancer. Genomic-guided treatment and efficacy prediction using molecular biomarkers in perioperative treatment are of great importance in the evolution of treatment and may become an ideal treatment method.

Quantitative multimodality imaging in cancer research and therapy

Advances in hardware and software have enabled the realization of clinically feasible, quantitative multimodality imaging of tissue pathophysiology. Earlier efforts relating to multimodality imaging of cancer have focused on the integration of anatomical and functional characteristics, such as PET-CT and single-photon emission CT (SPECT-CT), whereas more-recent advances and applications have involved the integration of multiple quantitative, functional measurements (for example, multiple PET tracers, varied MRI contrast mechanisms, and PET-MRI), thereby providing a more-comprehensive characterization of the tumour phenotype. The enormous amount of complementary quantitative data generated by such studies is beginning to offer unique insights into opportunities to optimize care for individual patients. Although important technical optimization and improved biological interpretation of multimodality imaging findings are needed, this approach can already be applied informatively in clinical trials of cancer therapeutics using existing tools. These concepts are discussed herein.