Bladder tumor is the most common malignant tumor in urinary system and always com- panied with lymph node metastasis. The accurate staging plays a significant role in treatment for bladder tumor and prognostic evaluat...Bladder tumor is the most common malignant tumor in urinary system and always com- panied with lymph node metastasis. The accurate staging plays a significant role in treatment for bladder tumor and prognostic evaluation, and the distant metastasis predicts worse prognosis. The objective of this study was to assess the clinical significance of 18F-FDG PET/CT imaging in diagnosing bladder tumor metastasis lesions. A retrospective analysis of 60 patients with bladder tumor from October 2008 to May 2010 was done. The patients were stratified based on the imaging technique. Among all 60 cases, besides the primary lesion, 81 suspected lesions were spotted and 73 confirmed as metastasis, including 50 lymph node metastases, 22 distant metastases, and 1 bone metastasis. For PET/CT imaging, its sensitivity was 94.5%, specificity 87.5%, positive predictive value 98.6%, negative predictive value 63.6% and accuracy 93.8% respectively. For CT, its sensitivity was 82.2%, specificity 50%, positive predictive value 93.8%, negative predictive value 23.5% and accuracy 79% respectively. PET/CT im- aging was superior to CT in sensitivity, specificity and accuracy. In conclusion, 18F-FDG PET/CT imaging is more significant in diagnosing bladder tumor metastasis lesions.展开更多
Liver tumor is the fifth most occurring type of tumor in men and the ninth most occurring type of tumor in women according to recent reports of Global cancer statistics 2018.There are several imaging tests like Comput...Liver tumor is the fifth most occurring type of tumor in men and the ninth most occurring type of tumor in women according to recent reports of Global cancer statistics 2018.There are several imaging tests like Computed Tomography(CT),Magnetic Resonance Imaging(MRI),and ultrasound that can diagnose the liver tumor after taking the sample from the tissue of the liver.These tests are costly and time-consuming.This paper proposed that image processing through deep learning Convolutional Neural Network(CNNs)ResUNet model that can be helpful for the early diagnose of tumor instead of conventional methods.The existing studies have mainly used the two Cascaded CNNs for liver segmentation and evaluation of Region Of Interest(ROI).This study uses ResUNet,an updated version of U-Net and ResNet Models that utilize the service of Residential blocks.We apply over method on the 3D-IRCADb01 dataset that is based on CT slices of liver tumor affected patients.The results showed the True Value Accuracy around 99%and F1 score performance around 95%.This method will be helpful for early and accurate diagnose of the Liver tumor to save the lives of many patients in the field of Biotechnology.展开更多
文摘Bladder tumor is the most common malignant tumor in urinary system and always com- panied with lymph node metastasis. The accurate staging plays a significant role in treatment for bladder tumor and prognostic evaluation, and the distant metastasis predicts worse prognosis. The objective of this study was to assess the clinical significance of 18F-FDG PET/CT imaging in diagnosing bladder tumor metastasis lesions. A retrospective analysis of 60 patients with bladder tumor from October 2008 to May 2010 was done. The patients were stratified based on the imaging technique. Among all 60 cases, besides the primary lesion, 81 suspected lesions were spotted and 73 confirmed as metastasis, including 50 lymph node metastases, 22 distant metastases, and 1 bone metastasis. For PET/CT imaging, its sensitivity was 94.5%, specificity 87.5%, positive predictive value 98.6%, negative predictive value 63.6% and accuracy 93.8% respectively. For CT, its sensitivity was 82.2%, specificity 50%, positive predictive value 93.8%, negative predictive value 23.5% and accuracy 79% respectively. PET/CT im- aging was superior to CT in sensitivity, specificity and accuracy. In conclusion, 18F-FDG PET/CT imaging is more significant in diagnosing bladder tumor metastasis lesions.
基金The authors extend their appreciation to the Deanship of Scientific Research at King Saud University for funding this work through research group No RG-1438-089.
文摘Liver tumor is the fifth most occurring type of tumor in men and the ninth most occurring type of tumor in women according to recent reports of Global cancer statistics 2018.There are several imaging tests like Computed Tomography(CT),Magnetic Resonance Imaging(MRI),and ultrasound that can diagnose the liver tumor after taking the sample from the tissue of the liver.These tests are costly and time-consuming.This paper proposed that image processing through deep learning Convolutional Neural Network(CNNs)ResUNet model that can be helpful for the early diagnose of tumor instead of conventional methods.The existing studies have mainly used the two Cascaded CNNs for liver segmentation and evaluation of Region Of Interest(ROI).This study uses ResUNet,an updated version of U-Net and ResNet Models that utilize the service of Residential blocks.We apply over method on the 3D-IRCADb01 dataset that is based on CT slices of liver tumor affected patients.The results showed the True Value Accuracy around 99%and F1 score performance around 95%.This method will be helpful for early and accurate diagnose of the Liver tumor to save the lives of many patients in the field of Biotechnology.
