2014
DOI: 10.3233/xst-140448
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Value of diffusion-weighted magnetic resonance imaging on the follow-up of nasopharyngeal carcinoma after radiotherapy

Abstract: PURPOSE: To explore the value of diffusion-weighted imaging (DWI) and magnetic resonance imaging (MRI) on the followup of nasopharyngeal carcinoma (NPC) after radiotherapy. MATERIAL AND METHODS: Eighty-three NPC patients after radiotherapy were divided into two groups: 4 cases of residual tumor and 33 cases of non-residual within 6 months, the cases of recurrent and non-recurrent were 5 and 41 over 6 months, respectively. MRI and DWI imaging of these cases were closely analyzed, and the apparent diffusion coef… Show more

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Cited by 9 publications
(6 citation statements)
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“…MR-DWI enables non-invasive in vivo assessment of the intrinsic biological characteristics of tissues, and has proven value for differential diagnosis 31 , staging 32 , monitoring the response to therapy 7 33 , prognostic evaluation 10 34 and early detection of recurrence 35 in many malignancies. Several studies have demonstrated high pretreatment ADC values correlate with unfavorable treatment responses or poor survival after radiotherapy and/or chemotherapy in various tumor types including breast cancer 36 , brain tumor 37 , bladder cancer 38 and some head and neck cancers 10 .…”
Section: Discussionmentioning
confidence: 99%
“…MR-DWI enables non-invasive in vivo assessment of the intrinsic biological characteristics of tissues, and has proven value for differential diagnosis 31 , staging 32 , monitoring the response to therapy 7 33 , prognostic evaluation 10 34 and early detection of recurrence 35 in many malignancies. Several studies have demonstrated high pretreatment ADC values correlate with unfavorable treatment responses or poor survival after radiotherapy and/or chemotherapy in various tumor types including breast cancer 36 , brain tumor 37 , bladder cancer 38 and some head and neck cancers 10 .…”
Section: Discussionmentioning
confidence: 99%
“…In recent years, deep learning methods have been widely used. For example, stacked autoencoders (SAEs) [ 14 ], deep belief networks (DBNs) [ 15 ], restricted Boltzmann machines (RBMs) [ 16 ], recurrent neural networks (RNNs) [ 17 ], and convolutional neural networks (CNNs) [ 18 ] have become the most popular deep learning algorithms. Melendez et al applied various learning techniques to detect chest X-ray tuberculosis with an area under the curve (AUC) of 0.86.…”
Section: Related Workmentioning
confidence: 99%
“…[ 5 ] The major reason is that the recurrent tumor after NPC radiotherapy and the nonrecurrent lesion both show slightly longer T1 and T2 signals in conventional MRI, and show different enhancement in enhanced scanning. [ 12 , 15 , 18 ] Therefore, using conventional MRI makes very difficult to clearly diagnose early recurrent tumors and multiple follow-ups are needed to observe the changes of the nasopharyngeal cavity. The present study showed that the sensitivity and specificity of conventional MRI in diagnosing local and clivus recurrent NPC were both relatively low (71.79% and 74.51% for locally recurrent NPC, and 63.63% and 47.91% for clivus recurrent NPC).…”
Section: Discussionmentioning
confidence: 99%
“…This technique can detect early pathological changes related with the changes of water volume in tissues. [ 18 , 21 ] Previous studies have shown that ADC values of tumors are positively associated with the differentiation of tumor cells. [ 10 , 12 16 , 22 , 23 ] DWI has already been applied in the diagnosis of prostate, breast, and liver diseases.…”
Section: Discussionmentioning
confidence: 99%