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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.

To assess the role of preoperative multiparametric MRI (mpMRI) of the prostate in the prediction of nodal metastases in patients treated with radical prostatectomy (RP) and extended pelvic lymph node dissection (ePLND). We retrospectively analyzed 101 patients who underwent both preoperative mpMRI of the prostate and RP with ePLND at our institution. For each patient, complete preoperative clinical data and tumour characteristics at mpMRI were recorded. Final histopathologic stage was considered the standard of reference. Univariate and multivariate logistic regression analyses were performed. Nodal metastases were found in 23/101 (22.8%) patients. At univariate analyses, all clinical and radiological parameters were significantly associated to nodal invasion (all p

To assess changes in apparent diffusion coefficient (ΔADC) and volume (ΔV) after neoadjuvant treatment (NT), and tumour regression grade (TRG) in gastro-oesophageal cancers (GEC), and to discriminate responders from non-responders.Thirty-two patients with biopsy-proven locally-advanced GEC underwent diffusion weighted magnetic resonance imaging (DWI) pre- and post-NT. Lesion ADC, volume, ΔADC and ΔV were calculated. TRG 1-2-3 patients were classified as R; TRG 4-5 as non-responders. ΔADC-TRG and ΔV-TRG correlations, pre-NT and post-NT ADC, ΔADC and ΔV cut-off values for responders and non-responders were calculated. Two readers measured mean tumour ADCs and interobserver variability was calculated. (Spearman's and intraclass correlation coefficient [ICC]).The interobserver reproducibility was very good both for pre-NT (Spearman's rho = 0.8160; ICC = 0.8993) and post-NT (Spearman's rho = 0.8357; ICC = 0.8663). Responders showed lower pre-NT ADC (1.32 versus 1.63 × 10(-3) mm(2)/s; P = 0.002) and higher post-NT ADC (2.22 versus 1.51 × 10(-3) mm(2)/s; P = 0.001) than non-responders and ADC increased in responders (ΔADC, 85.45 versus -8.21 %; P = 0.00005). ΔADC inversely correlated with TRG (r = -0.71, P = 0.000004); no difference in ΔV between responders and non-responders (-50.92 % versus -14.12 %; P = 0.068) and no correlation ΔV-TRG (r = 0.02 P = 0.883) were observed.The ADC can be used to assess gastro-oesophageal tumour response to neoadjuvant treatment as a reliable expression of tumour regression.• DWI is now being used to assess many cancers. • Change in ADC measurements offer new information about oesophageal tumours. • ADC changes are more reliable than dimensional criteria in assessing neoadjuvant treatment. • Such ADC assessment could optimise management of locally advanced gastro-oesophageal cancers.