Damiano Chiari

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

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

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.

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.

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.

Effect of neoadjuvant chemotherapy on HER-2 expression in surgically treated gastric and oesophagogastric junction carcinoma: a multicentre Italian study

Predictors of response to neoadjuvant chemotherapy are not available for gastric and oesophago-gastric junction carcinoma. HER-2 over-expression in breast cancer correlates with poor prognosis and high incidence of recurrence. First aim of this study was to evaluate if the HER-2 expression/amplification is predictive of response to neoadjuvant chemotherapy in terms of pathologic regression. Secondary aim was to evaluate if HER-2 expression varies after neoadjuvant treatment. Thirty-five patients with locally advanced gastric or oesophago-gastric junction carcinoma underwent preoperative chemotherapy and surgical resection at San Raffaele Scientific Institute and Spedali Civili of Brescia. HER-2 expression/amplification was evaluated on every biopsy at diagnosis time and on every surgical sample after neoadjuvant chemotherapy. Pathologic response to chemotherapy was evaluated according to TNM classification (ypT status and ypN status) and Mandard’s tumour regression grade classification. In our series 10 patients (28.6%) showed a reduction in HER-2 overexpression and in 6 of them (17.1%) HER-2 expression completely disappeared. Only three of the six patients with HER-2 disappearance had a complete pathological response to neoadjuvant chemotherapy. There was a strong correlation between HER-2 negativity on biopsy and absence of lymph node metastasis in surgical samples after neoadjuvant chemotherapy, irrespective of nodal status before chemotherapy. A direct correlation between HER-2 reduction after neoadjuvant chemotherapy and pathologic regression (primary tumour and lymph nodes) in surgical samples was found. HER-2 negativity may represent a predictor of pathologic response to neoadjuvant chemotherapy for gastric and oesophago-gastric junction adenocarcinoma. Neoadjuvant treatment can reduce HER-2 overexpression.