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Combined Volumetric and Density Analyses of Contrast-Enhanced CT Imaging to Assess Drug Therapy Response in Gastroenteropancreatic Neuroendocrine Diffuse Liver Metastasis.
Objective: We propose a computer-aided method to assess response to drug treatment, using CT imaging-based volumetric and density measures in patients with gastroenteropancreatic neuroendocrine tumors (GEP-NETs) and diffuse liver metastases.
Methods: Twenty-five patients with GEP-NETs with diffuse liver metastases were enrolled. Pre- and posttreatment CT examinations were retrospectively analyzed. Total tumor volume (volume) and mean volumetric tumor density (density) were calculated based on tumor segmentation on CT images. The maximum axial diameter (tumor size) for each target tumor was measured on pre- and posttreatment CT images according to Response Evaluation Criteria In Solid Tumors (RECIST). Progression-free survival (PFS) for each patient was measured and recorded.
Results: Correlation analysis showed inverse correlation between change of volume and density (Δ( V + D )), change of volume (Δ V ), and change of tumor size (Δ S ) with PFS ( r = -0.653, P =0.001; r = -0.617, P =0.003; r = -0.548, P =0.01, respectively). There was no linear correlation between Δ D and PFS ( r = -0.226, P =0.325).
Conclusion: The changes of volume and density derived from CT images of all lesions showed a good correlation with PFS and may help assess treatment response.
Methods: Twenty-five patients with GEP-NETs with diffuse liver metastases were enrolled. Pre- and posttreatment CT examinations were retrospectively analyzed. Total tumor volume (volume) and mean volumetric tumor density (density) were calculated based on tumor segmentation on CT images. The maximum axial diameter (tumor size) for each target tumor was measured on pre- and posttreatment CT images according to Response Evaluation Criteria In Solid Tumors (RECIST). Progression-free survival (PFS) for each patient was measured and recorded.
Results: Correlation analysis showed inverse correlation between change of volume and density (Δ( V + D )), change of volume (Δ V ), and change of tumor size (Δ S ) with PFS ( r = -0.653, P =0.001; r = -0.617, P =0.003; r = -0.548, P =0.01, respectively). There was no linear correlation between Δ D and PFS ( r = -0.226, P =0.325).
Conclusion: The changes of volume and density derived from CT images of all lesions showed a good correlation with PFS and may help assess treatment response.
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