Value of Triphasic MDCT in the Differentiation of Small Renal Cell Carcinoma and Oncocytoma

2017 ◽  
Vol 84 (4) ◽  
pp. 244-250
Author(s):  
Michele Scialpi ◽  
Eugenio Martorana ◽  
Valeria Rondoni ◽  
Ahmed Eissa ◽  
Ahmed El Sherbiny ◽  
...  
Keyword(s):  
Cell Carcinoma ◽  
Renal Clear Cell Carcinoma ◽  
Renal Tumors ◽  
Renal Oncocytoma ◽  
Multidetector Row Computed Tomography ◽  
Computed Tomographic ◽  
Unenhanced Ct ◽  
Significant Difference ◽  
Upper Abdomen

Introduction Although differentiation between benign and malignant small renal tumors (≤4 cm) is still difficult, it is a demand for decision making and determining the treatment strategy. Our aim is to evaluate the role of multidetector row computed tomography (MDCT) in the differentiation of small renal clear cell carcinoma (RCC) and renal oncocytoma (RO). Methods We reviewed triphasic computed tomographic (CT) scans performed in 43 patients diagnosed with RCC (n = 23) and RO (n = 21). After an unenhanced CT phase of the upper abdomen, triple-phase acquisition included a cortico-medullary phase (CMP), a nephrographic phase (NP), and a pyelographic phase (PP), and lesions were evaluated both qualitatively and quantitatively. Results RCCs were hypervascular in 13 cases and hypovascular in 10 cases, while ROs were hypervascular in nine cases and hypovascular in 12 cases. Mean attenuation values (MAVs) for hypervascular RCCs and hypervascular ROs on unenhanced examination were 34.0 ± 7.1 and 31.3 ± 8.1 HU, respectively. Enhancement in CMP was 173.1 ± 45.2 HU for RCCs and 151.1 ± 36.0 HU for ROs and a gradual wash-out in NP (148.8 ± 34.3 and 137.1 ± 33.9 HU for RCCs and ROs, respectively) and in PP (98.2 ± 36.0 HU for RCCs and 79.4 ± 21.5 HU for ROs) was observed. MAV for hypovascular RCCs and hypovascular ROs on unenhanced examination were 32.4 ± 12.0 and 28.9 ± 8.0 HU, respectively. Both hypovascular RCCs and ROs showed a statistically significant difference in each post contrastographic phase. Conclusions Absolute attenuation and the quantitative amount of the enhancement were not strong predictors for RO and RCC differentiation.

Parafibromin as a new immunohistochemistry staining to improve pathologic diagnosis of renal oncocytoma: Analysis of 225 renal tumors.

2011 ◽  
Vol 29 (7_suppl) ◽  
pp. 408-408 ◽  
Author(s):  
L. Albiges ◽  
J. Couturier ◽  
Y. Allory ◽  
P. Camparo ◽  
M. Sibony ◽  
...  
Keyword(s):  
Cell Carcinoma ◽  
Renal Cell ◽  
Renal Tumor ◽  
Diagnostic Value ◽  
Renal Clear Cell Carcinoma ◽  
Renal Tumors ◽  
Renal Oncocytoma ◽  
Positive Staining ◽  
Tissue Micro Array ◽  
Tumor Subtypes

408 Background: Chromophobe renal cell carcinoma (chRCC) and renal oncocytoma (Onc) are two distinct but closely related entities with strong morphologic and genetic similarities. While chRCC is a malignant tumor, Onc is usually considered as a benign entity. Recently, gene expression profiling applied on chRCC and Onc identified new potential markers that may effectively discriminate the 2 pathologic entities, including parafibromin. This work aims at evaluating the diagnostic value of Parafibromin (Pf) immuno staining on a large number of renal tumor samples. Methods: Sixty-three renal clear cell carcinoma (ccRCC), 47 papillary (Pap), 40 chRCC, and 75 Onc were immunostained for parafibromin antibody (1/200; Santacruz Biotechnology), on a tissue micro array. Results: Parafibromin was positive in 38.6% of Onc, vs 5% of chRCC (p < 0.001), with a 95% specificity, and the positive predictive value observed for parafibromin was 94%. For other tumor types, a positive staining for parafibromin was observed in 7.9% and 8.5% in ccRCC and Pap respectively. Conclusions: Parafibromin is a recently identified protein which seems to be specific for oncocytoma, and highly discriminant for other histologic renal cell tumor subtypes, especially for chromophobe. IHC may help to optimize therapeutics strategy for small renal mass and avoid surgical resection of benign lesions in some patients.Validation of this staining on renal tumor biopsies is on going.The value of the combination of this new immunostaining associated with the three standard IHC staining (CK7, CD117, E Cad) will be provided at the meeting. [Table: see text] No significant financial relationships to disclose.

scholarly journals Value of radiomics in differential diagnosis of chromophobe renal cell carcinoma and renal oncocytoma

2019 ◽  
Vol 45 (10) ◽  
pp. 3193-3201 ◽  
Author(s):  
Yajuan Li ◽  
Xialing Huang ◽  
Yuwei Xia ◽  
Liling Long
Keyword(s):  
Machine Learning ◽  
Differential Diagnosis ◽  
Cell Carcinoma ◽  
Area Under The Curve ◽  
Image Features ◽  
Renal Tumors ◽  
Support Vector ◽  
Svm Classifier ◽  
Renal Oncocytoma ◽  
Lasso Regression

Abstract Purpose To explore the value of CT-enhanced quantitative features combined with machine learning for differential diagnosis of renal chromophobe cell carcinoma (chRCC) and renal oncocytoma (RO). Methods Sixty-one cases of renal tumors (chRCC = 44; RO = 17) that were pathologically confirmed at our hospital between 2008 and 2018 were retrospectively analyzed. All patients had undergone preoperative enhanced CT scans including the corticomedullary (CMP), nephrographic (NP), and excretory phases (EP) of contrast enhancement. Volumes of interest (VOIs), including lesions on the images, were manually delineated using the RadCloud platform. A LASSO regression algorithm was used to screen the image features extracted from all VOIs. Five machine learning classifications were trained to distinguish chRCC from RO by using a fivefold cross-validation strategy. The performance of the classifier was mainly evaluated by areas under the receiver operating characteristic (ROC) curve and accuracy. Results In total, 1029 features were extracted from CMP, NP, and EP. The LASSO regression algorithm was used to screen out the four, four, and six best features, respectively, and eight features were selected when CMP and NP were combined. All five classifiers had good diagnostic performance, with area under the curve (AUC) values greater than 0.850, and support vector machine (SVM) classifier showed a diagnostic accuracy of 0.945 (AUC 0.964 ± 0.054; sensitivity 0.999; specificity 0.800), showing the best performance. Conclusions Accurate preoperative differential diagnosis of chRCC and RO can be facilitated by a combination of CT-enhanced quantitative features and machine learning.

scholarly journals The critical role of BAP1 mutation in the prognosis and treatment selection of kidney renal clear cell carcinoma

2020 ◽  
Vol 9 (4) ◽  
pp. 1725-1734
Author(s):  
Guobin Tan ◽  
Zijun Xuan ◽  
Zhiqin Li ◽  
Shuitong Huang ◽  
Guangming Chen ◽  
...  
Keyword(s):  
Cell Carcinoma ◽  
Clear Cell ◽  
Clear Cell Carcinoma ◽  
Critical Role ◽  
Renal Clear Cell Carcinoma ◽  
Treatment Selection ◽  
Selection Of

scholarly journals Role of Synaptophysin, Chromogranin and CD56 in adenocarcinoma and squamous cell carcinoma of the lung lacking morphological features of neuroendocrine differentiation: a retrospective large-scale study on 1170 tissue samples

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Katharina Kriegsmann ◽  
Christiane Zgorzelski ◽  
Thomas Muley ◽  
Petros Christopoulos ◽  
Michael Thomas ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Neuroendocrine Differentiation ◽  
Disease Free Survival ◽  
Morphological Features ◽  
Free Survival ◽  
Significant Difference ◽  
Disease Free

Abstract Background Synaptophysin, chromogranin and CD56 are recommended markers to identify pulmonary tumors with neuroendocrine differentiation. Whether the expression of these markers in pulmonary adenocarcinoma and pulmonary squamous cell carcinoma is a prognostic factor has been a matter of debate. Therefore, we investigated retrospectively a large cohort to expand the data on the role of synaptophysin, chromogranin and CD56 in non-small cell lung cancer lacking morphological features of neuroendocrine differentiation. Methods A cohort of 627 pulmonary adenocarcinomas (ADC) and 543 squamous cell carcinomas (SqCC) lacking morphological features of neuroendocrine differentiation was assembled and a tissue microarray was constructed. All cases were stained with synaptophysin, chromogranin and CD56. Positivity was defined as > 1% positive tumor cells. Data was correlated with clinico-pathological features including overall and disease free survival. Results 110 (18%) ADC and 80 (15%) SqCC were positive for either synaptophysin, chromogranin, CD56 or a combination. The most commonly positive single marker was synaptophysin. The least common positive marker was chromogranin. A combination of ≤2 neuroendocrine markers was positive in 2–3% of ADC and 0–1% of SqCC. There was no significant difference in overall survival in tumors with positivity for neuroendocrine markers neither in ADC (univariate: P = 0.4; hazard ratio [HR] = 0.867; multivariate: P = 0.5; HR = 0.876) nor in SqCC (univariate: P = 0.1; HR = 0.694; multivariate: P = 0.1, HR = 0.697). Likewise, there was no significant difference in disease free survival. Conclusions We report on a cohort of 1170 cases that synaptophysin, chromogranin and CD56 are commonly expressed in ADC and SqCC and that their expression has no impact on survival, supporting the current best practice guidelines.

scholarly journals Expression and Prognostic Role of MEKK3 and pERK in Patients with Renal Clear Cell Carcinoma

2015 ◽  
Vol 16 (6) ◽  
pp. 2495-2499 ◽  
Author(s):  
Qi Chen ◽  
Hong-sheng Lu ◽  
Mei-fu Gan ◽  
Lan-xi Chen ◽  
Kai He ◽  
...  
Keyword(s):  
Cell Carcinoma ◽  
Clear Cell ◽  
Clear Cell Carcinoma ◽  
Renal Clear Cell Carcinoma ◽  
Prognostic Role

scholarly journals Differentiation of Renal Oncocytoma and Renal Clear Cell Carcinoma Using Relative CT Enhancement Ratio

2015 ◽  
Vol 128 (2) ◽  
pp. 175-179 ◽  
Author(s):  
An Ren ◽  
Feng Cai ◽  
Yan-Ning Shang ◽  
En-Sen Ma ◽  
Zhen-Guo Huang ◽  
...  
Keyword(s):  
Cell Carcinoma ◽  
Clear Cell ◽  
Clear Cell Carcinoma ◽  
Renal Clear Cell Carcinoma ◽  
Renal Oncocytoma ◽  
Enhancement Ratio

scholarly journals T1a renal cell carcinoma on unenhanced CT: analysis of detectability and imaging features

2019 ◽  
Vol 8 (5) ◽  
pp. 205846011984970
Author(s):  
Aiko Gobara ◽  
Takeshi Yoshizako ◽  
Rika Yoshida ◽  
Megumi Nakamura ◽  
Hiroaki Shiina ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Tumor Size ◽  
Predictive Value ◽  
Renal Cell ◽  
Characteristic Curve ◽  
Imaging Features ◽  
Unenhanced Ct ◽  
Significant Difference ◽  
Ct Analysis

Background Increasing use of unenhanced computed tomography (CT) has been associated with the increasing incidental detection of renal cell carcinoma (RCC) at an earlier stage. Purpose To evaluate the characteristics in detecting and differentiating T1a RCCs on unenhanced CT. Material and Methods We retrospectively reviewed 68 patients with 68 T1a RCCs and 39 benign regions. Two radiologists interpreted the images on unenhanced axial CT and performed a blinded and independent review of T1a RCCs. The readers evaluated the presence of RCC and differentiated the detected lesions. Results The consensus of two readers detected 53 (78%) RCCs. Of the 53 detected RCCs, 42 (62%) RCCs were correctly diagnosed and 11 (16%) masses were misdiagnosed as benign. Of the 39 benign regions, 29 (74%) cysts were diagnosed correctly, but 10 (26%) cysts were misdiagnosed as malignant. The following values of the radiologists were obtained by consensus: sensitivity = 61.8% (42/68); specificity = 74.4% (29/39); positive predictive value = 80.8% (42/52); negative predictive value = 55.0% (29/55); accuracy = 66.4% (71/107). The receiver operating characteristic curve of consensus was 0.754. Inter-observer correlation was κ = 0.849. There was a significant difference in tumor size ( P = 0.019) and the contour type of tumor ( P = 0.0207) between correctly diagnosed RCCs and not correctly diagnosed RCCs. Conclusion Our findings showed that tumor size and contour type could affect the detection and differentiation of T1a RCC on unenhanced CT. To detect and differentiate T1a RCC on unenhanced CT is difficult. However, the findings from this study may help detection of RCCs on unenhanced CT.

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