Francesco Giganti1,2, Sofia Antunes3, Annalaura Salerno4,5, Alessandro Ambrosi5, Paolo Marra4,5, Roberto Nicoletti4, Elena Orsenigo6, Damiano Chiari5,6, Luca Albarello7, Carlo Staudacher5,6, Antonio Esposito4,5, Alessandro Del Maschio4,5, Francesco De Cobelli4,5. 1. Department of Radiology and Centre for Experimental Imaging San Raffaele Scientific Institute, Via Olgettina 60, 20132, Milan, Italy. giganti.fra@gmail.com. 2. San Raffaele Vita-Salute University, Milan, Italy. giganti.fra@gmail.com. 3. Centre for Experimental Imaging, San Raffaele Scientific Institute, Milan, Italy. 4. Department of Radiology and Centre for Experimental Imaging San Raffaele Scientific Institute, Via Olgettina 60, 20132, Milan, Italy. 5. San Raffaele Vita-Salute University, Milan, Italy. 6. Department of Surgery, San Raffaele Scientific Institute, Milan, Italy. 7. Pathology Unit, San Raffaele Scientific Institute, Milan, Italy.
Abstract
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.
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.
Entities:
Keywords:
Gastric cancer; Medical oncology; Multidetector computed tomography; Prognosis; Survival
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