Can multiphase CT scan distinguish between papillary renal cell carcinoma type 1 and type 2?

Bindayı, Ahmet; McDonald, Matthew J.; Beksaç, Alp Tuna; Rivera-Sanfeliz, Gerant; Shabaik, Ahmed; Cassidy, Fiona; Aganović, Lejla; Hansel, Donna E.; Derweesh, Ithaar

doi:10.5152/tud.2018.28938

Cited by 5 publications

(4 citation statements)

References 21 publications

(43 reference statements)

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“…Most papers [20][21][22][23][24][25][26][27][28][29] that have analyzed the association between attenuation values on MDCT and histological types have shown that the magnitude of enhancement at MDCT can help differentiate ccRCC from pRCC, chrRCC, and oncocytoma. Using measurements of quantitative MDCT enhancement values, our study showed that, among solid cortical renal tumors, the greatest utility in terms of differentiations was between ccRCC and pRCC.…”

Section: Discussionmentioning

confidence: 99%

Differentiation of Clear Cell Renal Cell Carcinoma from other Renal Cell Carcinoma Subtypes and Benign Oncocytoma Using Quantitative MDCT Enhancement Parameters

et al. 2020

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Background and objectives: The use of non-invasive techniques to predict the histological type of renal masses can avoid a renal mass biopsy, thus being of great clinical interest. The aim of our study was to assess if quantitative multiphasic multidetector computed tomography (MDCT) enhancement patterns of renal masses (malignant and benign) may be useful to enable lesion differentiation by their enhancement characteristics. Materials and Methods: A total of 154 renal tumors were retrospectively analyzed with a four-phase MDCT protocol. We studied attenuation values using the values within the most avidly enhancing portion of the tumor (2D analysis) and within the whole tumor volume (3D analysis). A region of interest (ROI) was also placed in the adjacent uninvolved renal cortex to calculate the relative tumor enhancement ratio. Results: Significant differences were noted in enhancement and de-enhancement (diminution of attenuation measurements between the postcontrast phases) values by histology. The highest areas under the receiver operating characteristic curves (AUCs) of 0.976 (95% CI: 0.924–0.995) and 0.827 (95% CI: 0.752–0.887), respectively, were demonstrated between clear cell renal cell carcinoma (ccRCC) and papillary RCC (pRCC)/oncocytoma. The 3D analysis allowed the differentiation of ccRCC from chromophobe RCC (chrRCC) with a AUC of 0.643 (95% CI: 0.555–0.724). Wash-out values proved useful only for discrimination between ccRCC and oncocytoma (43.34 vs 64.10, p < 0.001). However, the relative tumor enhancement ratio (corticomedullary (CM) and nephrographic phases) proved useful for discrimination between ccRCC, pRCC, and chrRCC, with the values from the CM phase having higher AUCs of 0.973 (95% CI: 0.929–0.993) and 0.799 (95% CI: 0.721–0.864), respectively. Conclusions: Our observations point out that imaging features may contribute to providing prognostic information helpful in the management strategy of renal masses.

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Section: Discussionmentioning

confidence: 99%

Differentiation of Clear Cell Renal Cell Carcinoma from other Renal Cell Carcinoma Subtypes and Benign Oncocytoma Using Quantitative MDCT Enhancement Parameters

et al. 2020

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“…Cognizance incorporates each psychological cycle that can be depicted as another experience. 34 On the off chance that AI technique with cognitive framework required to break down a major information data, the artificial intelligence strategy performs well while resolving action depending on given data, while the cognitive framework gives certain data to the client to select a superior outcome. 35 In setting autonomous, completely deterministic frameworks, for example, chess-playing, each activity in every particular state consistently creates a similar outcome and the outcome just relies upon the present status and the current activity, so they do not have to monitor past states.…”

Section: Methodsmentioning

confidence: 99%

“…We can promote intelligence by thinking, figuring out, summoning, and learning. Cognizance incorporates each psychological cycle that can be depicted as another experience 34 . On the off chance that AI technique with cognitive framework required to break down a major information data, the artificial intelligence strategy performs well while resolving action depending on given data, while the cognitive framework gives certain data to the client to select a superior outcome 35 .…”

Section: Methodsmentioning

confidence: 99%

Traffic prediction using MSSBiLS with self‐attention model

Suvitha

Vijayalakshmi

2022

Concurrency and Computation

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Due to gathering and examining a tremendous amount of traffic stream data, traffic blockage is the most important issue in the intelligent transportation framework. The main aim of this research work is "to find the appropriate deep learning time series models, to predict the future traffic of Denmark Aarhus city." In this article, multivariate sequential stacked bidirectional LSTM with self-attention model (MSSBiLS-SA) is proposed to prevent the long term dependencies and also to reduce the error rate.Based on the traffic state, the high, medium, and low range of traffic is predicted to give the best route to the users, and visualization is performed with the help of the Android application. The proposed MSSBiLS-SA attains higher accuracy 94.56% and 95.36%, sensitivity 88.74% and 92.5%, specificity 93.5% and 94.5%, precision 94.23% and 95.5%, F-score 94.5% and 94.5%, and lower time complexity 10.19% and 12.43% shows better performance when compared with the existing methods, such as prediction and classification of traffic location analysis using optimized graph convolutional recurrent neural network and prediction and classification of traffic location analysis based multilayer perceptron network using long short term memory. Finally, the proposed method predicts and classifies the traffic location very accurately.

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“…The CT manifestation of cystic renal cell carcinoma has high density resolution. Thus, the characteristics of cystic renal cell carcinoma can be analyzed by imaging, which helps to accurately diagnose cystic renal cell carcinoma (5). However, the CT manifestation of cystic renal cell carcinoma is similar to that of other benign cystic lesion.…”

Section: Introductionmentioning

confidence: 99%

Diagnostic value and clinical significance of ultrasound combined with CT in cystic renal cell carcinoma

et al. 2019

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This study investigated the value and clinical significance of ultrasound combined with CT in the diagnosis of cystic renal cell carcinoma. A total of 85 patients with cystic renal cell carcinoma, who were admitted to the Oncology Department of Yantai Yuhuangding Hospital Affiliated to Qingdao University from December 2015 to April 2017, were selected as the study group, and 70 patients with benign renal cyst, who were examined in Yantai Yuhuangding Hospital Affiliated to Qingdao University, were selected as the benign group. The patients in the two groups were examined by ultrasound and CT. The diagnostic value of ultrasound, CT, and ultrasound combined with CT in cystic renal cell carcinoma was analyzed. The sensitivity of ultrasound combined with CT was significantly higher than that of CT and ultrasound (P<0.05). The specificity and diagnostic coincidence rate of ultrasound combined with CT were significantly higher than those of CT (P<0.05). For unicapsular kidney cancer, there was no significant difference among ultrasound, CT and ultrasound combined with CT in the diagnosis of septum and wall nodule (P>0.05). For polycystic kidney cancer, there was no significant difference among ultrasound, CT and ultrasound combined with CT in the diagnosis of the presence or absence of septum (P>0.05). Ultrasound was significantly better than CT in cyst wall confounding (P<0.05). Ultrasound combined with CT was significantly better than ultrasound in calcification and blood supply of tumors (P<0.05). In conclusion, the accuracy of ultrasound combined with CT is higher than that of ultrasound or that of CT in the diagnosis of cystic renal cell carcinoma, which can be beneficial in accurately carrying out clinical diagnosis, reduce the incidence of missed diagnosis and misdiagnosis caused by a single diagnosis and treatment. Ultrasound combined with CT is good for clinical screening and can guide clinical symptomatic treatment, which is worthy of generalizing in clinic.

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Can multiphase CT scan distinguish between papillary renal cell carcinoma type 1 and type 2?

Cited by 5 publications

References 21 publications

Differentiation of Clear Cell Renal Cell Carcinoma from other Renal Cell Carcinoma Subtypes and Benign Oncocytoma Using Quantitative MDCT Enhancement Parameters

Differentiation of Clear Cell Renal Cell Carcinoma from other Renal Cell Carcinoma Subtypes and Benign Oncocytoma Using Quantitative MDCT Enhancement Parameters

Traffic prediction using MSSBiLS with self‐attention model

Diagnostic value and clinical significance of ultrasound combined with CT in cystic renal cell carcinoma

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