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Intravoxel incoherent motion imaging for predicting pathological complete response of locally advanced rectal cancer after neoadjuvant chemotherapy / 中国医学影像技术
Chinese Journal of Medical Imaging Technology ; (12): 372-377, 2018.
Artículo en Chino | WPRIM | ID: wpr-706244
ABSTRACT
Objective To explore the value of intravoxel incoherent motion (IVIM) analysis in evaluation of pathological complete response (pCR) in patients with locally advanced rectal cancer (LARC) after neoadjuvant chemotherapy.Methods Totally 61 patients with pathologically proven rectal adenocarcinoma were retrospectively analyzed.All patients underwent MR scan,including multi-b DWI IVIM sequence scanning before and after neoadjuvant chemotherapy.ADC values and IVIM parameters (slow diffusion coefficient [D],fast diffusion coefficient [D*] and perfusion fraction [f]) were measured by two radiologists independently.Then the patients were divided into pCR group (n=14) and non-pCR group (n=47).Independent-samples t test was used to compare all the parameters before and after therapy,as well as the percentage changes (△ratio) between pCR and non-pCR group.Area under the curve (AUC) was used to evaluate the diagnostic performance.Results ADC (P=0.002) and D (P=0.007) values were significantly lower before therapy,while △ratio ADC (P<0.001) and △ratio D (P =0.002) were significantly higher in pCR group compared with those in non-pCR group.D*,f and their △ratio value were not statistically different pre-chemotherapy and post-chemotherapy in both two groups (all P>0.05).△ratio D had the highest AUC (0.786,P<0.01).Conclusion IVIM-derived D values can help to predict and differentiate pCR of LARC after neoadjuvant chemotherapy.

Texto completo: Disponible Índice: WPRIM (Pacífico Occidental) Tipo de estudio: Estudio pronóstico Idioma: Chino Revista: Chinese Journal of Medical Imaging Technology Año: 2018 Tipo del documento: Artículo

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Texto completo: Disponible Índice: WPRIM (Pacífico Occidental) Tipo de estudio: Estudio pronóstico Idioma: Chino Revista: Chinese Journal of Medical Imaging Technology Año: 2018 Tipo del documento: Artículo