CT differentiation of the oncocytoma and renal cell carcinoma based on peripheral tumor parenchyma and central hypodense area characterisation
Abstract Background Although the central scar is an essential imaging characteristic of renal oncocytoma (RO), its utility in distinguishing RO from renal cell carcinoma (RCC) has not been well explored. The study aimed to evaluate whether the combination of CT characteristics of the peripheral tumo...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2023-01-01
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| Series: | BMC Medical Imaging |
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| Online Access: | https://doi.org/10.1186/s12880-023-00972-0 |
| _version_ | 1811175704523440128 |
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| author | Jianyi Qu Qianqian Zhang Xinhong Song Hong Jiang Heng Ma Wenhua Li Xiaofei Wang |
| author_facet | Jianyi Qu Qianqian Zhang Xinhong Song Hong Jiang Heng Ma Wenhua Li Xiaofei Wang |
| author_sort | Jianyi Qu |
| collection | DOAJ |
| description | Abstract Background Although the central scar is an essential imaging characteristic of renal oncocytoma (RO), its utility in distinguishing RO from renal cell carcinoma (RCC) has not been well explored. The study aimed to evaluate whether the combination of CT characteristics of the peripheral tumor parenchyma (PTP) and central hypodense area (CHA) can differentiate typical RO with CHA from RCC. Methods A total of 132 tumors on the initial dataset were retrospectively evaluated using four-phase CT. The excretory phases were performed more than 20 min after the contrast injection. In corticomedullary phase (CMP) images, all tumors had CHAs. These tumors were categorized into RO (n = 23), clear cell RCC (ccRCC) (n = 85), and non-ccRCC (n = 24) groups. The differences in these qualitative and quantitative CT features of CHA and PTP between ROs and ccRCCs/non-ccRCCs were statistically examined. Logistic regression filters the main factors for separating ROs from ccRCCs/non-ccRCCs. The prediction models omitting and incorporating CHA features were constructed and evaluated, respectively. The effectiveness of the prediction models including CHA characteristics was then confirmed through a validation dataset (8 ROs, 35 ccRCCs, and 10 non-ccRCCs). Results The findings indicate that for differentiating ROs from ccRCCs and non-ccRCCs, prediction models with CHA characteristics surpassed models without CHA, with the corresponding areas under the curve (AUC) being 0.962 and 0.914 versus 0.952 and 0.839 respectively. In the prediction models that included CHA parameters, the relative enhancement ratio (RER) in CMP and enhancement inversion, as well as RER in nephrographic phase and enhancement inversion were the primary drivers for differentiating ROs from ccRCCs and non-ccRCCs, respectively. The prediction models with CHA characteristics had the comparable diagnostic ability on the validation dataset, with respective AUC values of 0.936 and 0.938 for differentiating ROs from ccRCCs and non-ccRCCs. Conclusion The prediction models with CHA characteristics can help better differentiate typical ROs from RCCs. When a mass with CHA is discovered, particularly if RO is suspected, EP images with longer delay scanning periods should be acquired to evaluate the enhancement inversion characteristics of CHA. |
| first_indexed | 2024-04-10T19:40:05Z |
| format | Article |
| id | doaj.art-a2b950731bc4457386bcf16786c09843 |
| institution | Directory Open Access Journal |
| issn | 1471-2342 |
| language | English |
| last_indexed | 2024-04-10T19:40:05Z |
| publishDate | 2023-01-01 |
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| series | BMC Medical Imaging |
| spelling | doaj.art-a2b950731bc4457386bcf16786c098432023-01-29T12:24:47ZengBMCBMC Medical Imaging1471-23422023-01-0123111110.1186/s12880-023-00972-0CT differentiation of the oncocytoma and renal cell carcinoma based on peripheral tumor parenchyma and central hypodense area characterisationJianyi Qu0Qianqian Zhang1Xinhong Song2Hong Jiang3Heng Ma4Wenhua Li5Xiaofei Wang6Yuhuangding Hospital, Qingdao University School of MedicineYuhuangding Hospital, Qingdao University School of MedicineYuhuangding Hospital, Qingdao University School of MedicineYuhuangding Hospital, Qingdao University School of MedicineYuhuangding Hospital, Qingdao University School of MedicineXinhua Hospital, Shanghai Jiaotong University School of MedicineYantaishan Hospital, Binzhou Medical UniversityAbstract Background Although the central scar is an essential imaging characteristic of renal oncocytoma (RO), its utility in distinguishing RO from renal cell carcinoma (RCC) has not been well explored. The study aimed to evaluate whether the combination of CT characteristics of the peripheral tumor parenchyma (PTP) and central hypodense area (CHA) can differentiate typical RO with CHA from RCC. Methods A total of 132 tumors on the initial dataset were retrospectively evaluated using four-phase CT. The excretory phases were performed more than 20 min after the contrast injection. In corticomedullary phase (CMP) images, all tumors had CHAs. These tumors were categorized into RO (n = 23), clear cell RCC (ccRCC) (n = 85), and non-ccRCC (n = 24) groups. The differences in these qualitative and quantitative CT features of CHA and PTP between ROs and ccRCCs/non-ccRCCs were statistically examined. Logistic regression filters the main factors for separating ROs from ccRCCs/non-ccRCCs. The prediction models omitting and incorporating CHA features were constructed and evaluated, respectively. The effectiveness of the prediction models including CHA characteristics was then confirmed through a validation dataset (8 ROs, 35 ccRCCs, and 10 non-ccRCCs). Results The findings indicate that for differentiating ROs from ccRCCs and non-ccRCCs, prediction models with CHA characteristics surpassed models without CHA, with the corresponding areas under the curve (AUC) being 0.962 and 0.914 versus 0.952 and 0.839 respectively. In the prediction models that included CHA parameters, the relative enhancement ratio (RER) in CMP and enhancement inversion, as well as RER in nephrographic phase and enhancement inversion were the primary drivers for differentiating ROs from ccRCCs and non-ccRCCs, respectively. The prediction models with CHA characteristics had the comparable diagnostic ability on the validation dataset, with respective AUC values of 0.936 and 0.938 for differentiating ROs from ccRCCs and non-ccRCCs. Conclusion The prediction models with CHA characteristics can help better differentiate typical ROs from RCCs. When a mass with CHA is discovered, particularly if RO is suspected, EP images with longer delay scanning periods should be acquired to evaluate the enhancement inversion characteristics of CHA.https://doi.org/10.1186/s12880-023-00972-0OncocytomaRenal cell carcinomaCentral hypodense areaEnhancement inversionPeripheral tumor parenchymaCT |
| spellingShingle | Jianyi Qu Qianqian Zhang Xinhong Song Hong Jiang Heng Ma Wenhua Li Xiaofei Wang CT differentiation of the oncocytoma and renal cell carcinoma based on peripheral tumor parenchyma and central hypodense area characterisation BMC Medical Imaging Oncocytoma Renal cell carcinoma Central hypodense area Enhancement inversion Peripheral tumor parenchyma CT |
| title | CT differentiation of the oncocytoma and renal cell carcinoma based on peripheral tumor parenchyma and central hypodense area characterisation |
| title_full | CT differentiation of the oncocytoma and renal cell carcinoma based on peripheral tumor parenchyma and central hypodense area characterisation |
| title_fullStr | CT differentiation of the oncocytoma and renal cell carcinoma based on peripheral tumor parenchyma and central hypodense area characterisation |
| title_full_unstemmed | CT differentiation of the oncocytoma and renal cell carcinoma based on peripheral tumor parenchyma and central hypodense area characterisation |
| title_short | CT differentiation of the oncocytoma and renal cell carcinoma based on peripheral tumor parenchyma and central hypodense area characterisation |
| title_sort | ct differentiation of the oncocytoma and renal cell carcinoma based on peripheral tumor parenchyma and central hypodense area characterisation |
| topic | Oncocytoma Renal cell carcinoma Central hypodense area Enhancement inversion Peripheral tumor parenchyma CT |
| url | https://doi.org/10.1186/s12880-023-00972-0 |
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