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Dmitry F, Evgeniy S, Vasiliy K, Alexandra P, Khalil I, Evgeny S, Mikhail C, Kirill P, Alexander T, Dmitry K, Camilla A, Andrey V, Denis B, Petr G, Leonid R. Tumor morphology evaluation using 3D-morphometric features of renal masses. Urologia 2024:3915603241261499. [PMID: 39058231 DOI: 10.1177/03915603241261499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/28/2024]
Abstract
OBJECTIVE To assess the correlation between the general (gender, age, and maximum tumor size) and 3D morphotopometric features of the renal tumor node, following the MSCT data post-processing, and the tumor histological structure; to propose an equation allowing for kidney malignancy assessment based on general and morphometric features. MATERIALS AND METHODS In total, 304 patients with unilateral solitary renal neoplasms underwent laparoscopic (retroperitoneoscopic) or robotic partial or radical nephrectomy. Before the procedure, kidney contrast-enhanced MSCT followed by the tumor 3D-modeling was performed. 3D model of the kidney tumor, and its morphotopometric features, and histological structure were analyzed. The morphotopometric ones include the side of the lesion, location by segments, the surface where the tumor, the depth of the tumor invasion into the kidney, and the shape of tumor. RESULTS Out of 304 patients, 254 (83.6%) had malignant kidney tumors and 50 (16.4%) benign kidney tumors. In total, 231 patients, out of 254 (90.9%) were assessed for the degree of malignant tumor differentiation. Malignant tumors were more frequent in men than in women (p < 0.001). Mushroom-shaped tumors were the most common shapes among benign renal masses (35.2%). The most common malignant kidney tumors had spherical with a partially uneven surface (27.6%), multinodular (tuberous (27.2%)), and spherical with a conical base (24.8%) shapes. Logistic regression model enabled the development of prognostic equation for tumor malignancy prediction ("low" or "high"). The univariate analysis revealed the correlation only between high differentiation (G1) and a spherical tumor with a conical base (p = 0.029). CONCLUSION The resulting logistic model, based on the analysis of such predictors as gender and form of kidney lesions, demonstrated a large share (87.6%) of correct predictions of the kidney tumor malignancy.
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Affiliation(s)
- Fiev Dmitry
- Institute for Urology and Human Reproductive Health, Sechenov University, Moscow, Russia
| | - Sirota Evgeniy
- Institute for Urology and Human Reproductive Health, Sechenov University, Moscow, Russia
| | - Kozlov Vasiliy
- Semashko Department of Public Health and Healthcare, Sechenov University, Moscow, Russia
| | - Proskura Alexandra
- Institute for Urology and Human Reproductive Health, Sechenov University, Moscow, Russia
| | - Ismailov Khalil
- Institute for Urology and Human Reproductive Health, Sechenov University, Moscow, Russia
| | - Shpot Evgeny
- Institute for Urology and Human Reproductive Health, Sechenov University, Moscow, Russia
| | - Chernenkiy Mikhail
- Institute for Urology and Human Reproductive Health, Sechenov University, Moscow, Russia
| | - Puzakov Kirill
- Department of Radiology, The Second University Clinic, Sechenov University, Moscow, Russia
| | - Tarasov Alexander
- Institute of Linguistics and Intercultural Communication, Sechenov University, Moscow, Russia
| | - Korolev Dmitry
- Institute for Urology and Human Reproductive Health, Sechenov University, Moscow, Russia
| | - Azilgareeva Camilla
- Institute for Urology and Human Reproductive Health, Sechenov University, Moscow, Russia
| | - Vinarov Andrey
- Institute for Urology and Human Reproductive Health, Sechenov University, Moscow, Russia
| | - Butnaru Denis
- Institute for Urology and Human Reproductive Health, Sechenov University, Moscow, Russia
| | - Glybochko Petr
- Institute for Urology and Human Reproductive Health, Sechenov University, Moscow, Russia
| | - Rapoport Leonid
- Institute for Urology and Human Reproductive Health, Sechenov University, Moscow, Russia
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Chai JL, Siegmund SE, Hirsch MS, Silverman SG. Low-grade oncocytic tumor: a review of radiologic and clinical features. Abdom Radiol (NY) 2024; 49:1940-1948. [PMID: 38372764 DOI: 10.1007/s00261-023-04167-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 12/09/2023] [Accepted: 12/16/2023] [Indexed: 02/20/2024]
Abstract
PURPOSE The 2022 World Health Organization classification of renal neoplasia expanded the spectrum of oncocytic neoplasms to encompass newly established and emerging entities; one of the latter is the low-grade oncocytic tumor (LOT). This study reports the radiologic appearance and clinical behavior of LOT. METHODS In this IRB-approved, HIPPA-compliant retrospective study, our institution's pathology database was searched for low-grade oncocytic tumors or neoplasms. Patient age, gender, and comorbidities were obtained from a review of electronic medical records, and imaging characteristics of the tumors were assessed through an imaging platform. RESULTS The pathology database search yielded 14 tumors in 14 patients. Four patients were excluded, as radiologic images were not available in three, and one did not fulfill diagnostic criteria after pathology re-review. The resulting cohort consisted of 10 tumors (median diameter 2.3 cm, range 0.7-5.1) in 10 patients (median age 68 years, range 53-91, six women). All tumors presented as a solitary, well-circumscribed, mass with solid components. All enhanced as much or almost as much as adjacent renal parenchyma; all but one enhanced heterogeneously. None had lymphadenopathy, venous invasion, or metastatic disease at presentation or at clinical follow-up (median, 22.2 months, range 3.4-71.6). Among five tumors undergoing active surveillance, mean increase in size was 0.4 cm/year at imaging follow-up (median 16.7 months, range 8.9-25.4). CONCLUSION LOT, a recently described pathologic entity in the kidney, can be considered in the differential diagnosis of an avidly and typically heterogeneously enhancing solid renal mass in an adult patient.
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Affiliation(s)
- Jessie L Chai
- Division of Abdominal Imaging and Intervention, Department of Radiology, Brigham and Women's Hospital, 75 Francis St, Boston, MA, 02115, USA.
| | | | - Michelle S Hirsch
- Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA
| | - Stuart G Silverman
- Division of Abdominal Imaging and Intervention, Department of Radiology, Brigham and Women's Hospital, 75 Francis St, Boston, MA, 02115, USA
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Hao YW, Zhang Y, Guo HP, Xu W, Bai X, Zhao J, Ding XH, Gao S, Cui MQ, Liu BC, Ye HY, Wang HY. Differentiation between renal epithelioid angiomyolipoma and clear cell renal cell carcinoma using clear cell likelihood score. Abdom Radiol (NY) 2023; 48:3714-3727. [PMID: 37747536 DOI: 10.1007/s00261-023-04034-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 08/21/2023] [Accepted: 08/23/2023] [Indexed: 09/26/2023]
Abstract
PURPOSE Clear cell likelihood score (ccLS) may be a reliable diagnostic method for distinguishing renal epithelioid angiomyolipoma (EAML) and clear cell renal cell carcinoma (ccRCC). In this study, we aim to explore the value of ccLS in differentiating EAML from ccRCC. METHODS We performed a retrospective analysis in which 27 EAML patients and 60 ccRCC patients underwent preoperative magnetic resonance imaging (MRI) at our institution. Two radiologists trained in the ccLS algorithm scored independently and the consistency of their interpretation was evaluated. The difference of the ccLS score was compared between EAML and ccRCC in the whole study cohort and two subgroups [small renal masses (SRM; ≤ 4 cm) and large renal masses (LRM; > 4 cm)]. RESULTS In total, 87 patients (59 men, 28 women; mean age, 55±11 years) with 90 renal masses (EAML: ccRCC = 1: 2) were identified. The interobserver agreement of two radiologists for the ccLS system to differentiate EAML from ccRCC was good (k = 0.71). The ccLS score in the EAML group and the ccRCC group ranged from 1 to 5 (73.3% in scores 1-2) and 2 to 5 (76.7% in scores 4-5), respectively, with statistically significant differences (P < 0.001). With the threshold value of 2, ccLS can distinguish EAML from ccRCC with the accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 87.8%, 95.0%, 73.3%, 87.7%, and 88.0%, respectively. The AUC (area under the curve) was 0.913. And the distribution of the ccLS score between the two diseases was not affected by tumor size (P = 0.780). CONCLUSION The ccLS can distinguish EAML from ccRCC with high accuracy and efficiency.
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Affiliation(s)
- Yu-Wei Hao
- Department of Radiology, First Medical Center, Chinese PLA General Hospital, No. 28 Fuxing Road, Haidian District, Beijing, 100853, China
| | - Yun Zhang
- Department of Radiology, First Medical Center, Chinese PLA General Hospital, No. 28 Fuxing Road, Haidian District, Beijing, 100853, China
- Department of Radiology, Sixth Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Hui-Ping Guo
- Department of Radiology, First Medical Center, Chinese PLA General Hospital, No. 28 Fuxing Road, Haidian District, Beijing, 100853, China
| | - Wei Xu
- Department of Radiology, First Medical Center, Chinese PLA General Hospital, No. 28 Fuxing Road, Haidian District, Beijing, 100853, China
| | - Xu Bai
- Department of Radiology, First Medical Center, Chinese PLA General Hospital, No. 28 Fuxing Road, Haidian District, Beijing, 100853, China
| | - Jian Zhao
- Department of Radiology, First Medical Center, Chinese PLA General Hospital, No. 28 Fuxing Road, Haidian District, Beijing, 100853, China
| | - Xiao-Hui Ding
- Department of Pathology, First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Sheng Gao
- Department of Radiology, Linyi Central Hospital, Shandong, China
| | - Meng-Qiu Cui
- Department of Radiology, First Medical Center, Chinese PLA General Hospital, No. 28 Fuxing Road, Haidian District, Beijing, 100853, China
| | - Bai-Chuan Liu
- Department of Radiology, First Medical Center, Chinese PLA General Hospital, No. 28 Fuxing Road, Haidian District, Beijing, 100853, China
| | - Hui-Yi Ye
- Department of Radiology, First Medical Center, Chinese PLA General Hospital, No. 28 Fuxing Road, Haidian District, Beijing, 100853, China
| | - Hai-Yi Wang
- Department of Radiology, First Medical Center, Chinese PLA General Hospital, No. 28 Fuxing Road, Haidian District, Beijing, 100853, China.
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Nalbant MO, Inci E. Assessment of Imaging Findings of Renal Carcinoma Subtypes with 3.0T MRI. Niger J Clin Pract 2023; 26:1750-1757. [PMID: 38044783 DOI: 10.4103/njcp.njcp_373_23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 07/06/2023] [Indexed: 12/05/2023]
Abstract
BACKGROUND The prevalence of renal masses has escalated as a result of the augmented utilization of cross-sectional imaging techniques. The approach to managing renal masses may exhibit variability contingent upon the subtype of renal cell carcinoma (RCC). AIM This research aimed to distinguish between clear cell and papillary RCCs, utilizing dynamic contrast magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI). MATERIALS AND METHODS The study assessed the MR images of 112 patients with RCC. Two radiologists independently analyzed tumor size, vascular involvement, signal characteristics in T1- and T2-weighted sequences, the presence of hemosiderin, both microscopic and macroscopic fat content, enhancement patterns, and apparent diffusion coefficient (ADC) values derived from b-values of 1000 s/mm². RESULTS Seventy patients had clear cell RCC, and 42 had papillary. In the clear cell RCC, microscopic fat content was significantly higher than the papillary RCC (P < 0.001). However, in papillary RCC, hemosiderin content was substantially greater (P = 0.001). On T2-weighted MR images, clear cell RCCs were usually hyperintense, while papillary RCCs were hypointense (P < 0.001). Even though the rapid enhancement pattern was observed in clear cell RCCs, the progressive enhancement pattern was more prevalent in papillary RCCs (P < 0.001). CONCLUSION Hyperintensity on T2-weighted images, microscopic fat content, and rapid enhancement pattern may be indicative of clear cell RCC, whereas hypointensity on T2-weighted images, hemosiderin content, and a progressive contrast pattern may be diagnostic for papillary RCC.
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Affiliation(s)
- M O Nalbant
- Department of Radiology, University of Health Sciences, Bakirkoy Dr. Sadi Konuk Training and Research Hospital, Istanbul, Turkey
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MRI Characteristics of Pediatric and Young-Adult Renal Cell Carcinoma: A Single-Center Retrospective Study and Literature Review. Cancers (Basel) 2023; 15:cancers15051401. [PMID: 36900194 PMCID: PMC10000563 DOI: 10.3390/cancers15051401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 02/09/2023] [Accepted: 02/17/2023] [Indexed: 02/25/2023] Open
Abstract
Pediatric renal cell carcinoma (RCC) is a rare malignancy. Magnetic resonance imaging (MRI) is the preferred imaging modality for assessment of these tumors. The previous literature has suggested that cross-sectional-imaging findings differ between RCC and other pediatric renal tumors and between RCC subtypes. However, studies focusing on MRI characteristics are limited. Therefore, this study aims to identify MRI characteristics of pediatric and young-adult RCC, through a single-center case series and literature review. Six identified diagnostic MRI scans were retrospectively assessed, and an extensive literature review was conducted. The included patients had a median age of 12 years (63-193 months). Among other subtypes, 2/6 (33%) were translocation-type RCC (MiT-RCC) and 2/6 (33%) were clear-cell RCC. Median tumor volume was 393 cm3 (29-2191 cm3). Five tumors had a hypo-intense appearance on T2-weighted imaging, whereas 4/6 were iso-intense on T1-weighted imaging. Four/six tumors showed well-defined margins. The median apparent diffusion coefficient (ADC) values ranged from 0.70 to 1.20 × 10-3 mm2/s. In thirteen identified articles focusing on MRI characteristics of MiT-RCC, the majority of the patients also showed T2-weighted hypo-intensity. T1-weighted hyper-intensity, irregular growth pattern and limited diffusion-restriction were also often described. Discrimination of RCC subtypes and differentiation from other pediatric renal tumors based on MRI remains difficult. Nevertheless, T2-weighted hypo-intensity of the tumor seems a potential distinctive characteristic.
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Liu MC, Liu YJ, Lin YT, Hung SW, Chai JW, Chan SW, Chiu KY, Chang CH, Tsou YL. Common Subtype of Small Renal Mass MR Imaging Characterisation: A Medical Center Experience in Taiwan. J Med Biol Eng 2022. [DOI: 10.1007/s40846-022-00684-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
Abstract
Purpose
Many studies have shown that multiparametric magnetic resonance imaging (MRI) may be helpful for differentiating malignant renal cell carcinomas (RCCs) from benign lesions. However, the key imaging characteristics that differ between malignant and benign tumors still require further discussion.
Methods
We analyzed 60 adult patients diagnosed with 72 small renal masses (SRMs) who received preoperative MRI from 2014 to 2019 at a hospital in Taiwan. The MRI features included conventional MRI parameters, diffusion-weighted imaging (DWI) data, and dynamic contrast-enhanced (DCE) patterns, which were documented and compared among the four common subtypes: clear cell RCC (ccRCC), papillary RCC (pRCC), angiomyolipoma (AML) and other types of RCC. The apparent diffusion coefficient (ADC) values of high- and low-grade RCCs were also analyzed.
Results
The results show that ccRCC had higher T2-weighted signal intensity than the other three subgroups, a higher arterial wash-in index (AWI) and ADC value than AML and pRCC, and manifested a plateau (n = 9, 25%) or washout (n = 27, 75%) enhancement pattern. AMLs exhibited more intravoxel fat than the other three subtype groups, and half of the AMLs (6 in 12) contained bulk fat. pRCC demonstrated a more progressive (n = 3, 60%) enhancement pattern than the other three subgroups. The ADC value of high-grade RCCs was significantly lower than that of low-grade RCCs.
Conclusion
These findings may indicate that multiparametric MRI is useful in differentiating among four common pathological types of SRMs, and the ADC value may be helpful in evaluating the histological grade of malignancy.
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Zhang H, Wang P, Shi D, Yao X, Li Y, Liu X, Sun Y, Ding J, Wang S, Wang G, Ren K. Capability of intravoxel incoherent motion and diffusion tensor imaging to detect early kidney injury in type 2 diabetes. Eur Radiol 2022; 32:2988-2997. [PMID: 35031840 DOI: 10.1007/s00330-021-08415-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Revised: 10/11/2021] [Accepted: 10/13/2021] [Indexed: 11/28/2022]
Abstract
OBJECTIVES To prospectively investigate the capability of intravoxel incoherent motion (IVIM) and conventional diffusion tensor imaging (DTI) to identify early kidney function injury in type 2 diabetes. METHODS Forty-one diabetes patients (normoalbuminuria: n = 27; microalbuminuria: n = 14) and 28 volunteers were recruited. All participants were examined using DTI and IVIM with 3.0-T MRI. DTI parameters (mean diffusivity [MD], fractional anisotropy [FA]), and IVIM parameters (true diffusion coefficient [D], pseudo-diffusion coefficient [D*], and pseudo-diffusion component fraction [f]) were measured in the renal parenchyma (cortex and medulla) by two experienced radiologists independently. Image features were compared among the groups using separate one-way analyses of variance. Diagnostic performances of various diffusion parameters for predicting diabetic renal damage were compared. RESULTS The medullary D and FA values were significantly different among the microalbuminuria subgroup, normoalbuminuria subgroup, and control group (all p < 0.001). In medulla, area under the curve (AUC) values for combined FA and D were significantly higher than single FA (AUC = 0.938, 0.769, respectively; p = 0.003), and the combined AUC of FA and D was numerically higher than that of single D (0.938 vs 0.878, p > 0.05). AUC of combined FA and D was 0.985, not significantly different from individual AUC for FA and D (AUC = 0.909 and 0.952, respectively; all p > 0.05) in differentiating the microalbuminuria subgroup from the control group. CONCLUSION IVIM-derived D and DTI-derived FA values were better than other parameters for evaluating early kidney impairment of diabetes. The single indicator FA and D performed as well as the combined diagnostic indicator in the medulla for differentiating the microalbuminuria subgroup from the control group. KEY POINTS • We speculated that early renal progression in type 2 diabetes result from restricted tubular flow and kidney tubule dysregulation may precede or at least accompany abnormal glomerular changes. • In medulla, the AUC values of FA and D and the combination of FA and D obtained by comparing the microalbuminuria subgroup with the control group were 0.909, 0.952, and 0.985, respectively. • IVIM-derived D and DTI-derived FA are effective MR biomarkers to evaluate early alterations of the renal function in patients with diabetes.
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Affiliation(s)
- Haoran Zhang
- Department of Radiology, Xiang'an Hospital of Xiamen University, Xiamen, 361005, China
| | - Peng Wang
- Department of Radiology, The First Hospital of China Medical University, Shenyang, China
| | - Dafa Shi
- Department of Radiology, Xiang'an Hospital of Xiamen University, Xiamen, 361005, China
| | - Xiang Yao
- Department of Radiology, Xiang'an Hospital of Xiamen University, Xiamen, 361005, China
| | - Yanfei Li
- Department of Radiology, Xiang'an Hospital of Xiamen University, Xiamen, 361005, China
| | - Xuedan Liu
- Department of Radiology, Xiang'an Hospital of Xiamen University, Xiamen, 361005, China
| | - Yang Sun
- Department of Radiology, Xiang'an Hospital of Xiamen University, Xiamen, 361005, China
| | - Jie Ding
- Department of Radiology, Xiang'an Hospital of Xiamen University, Xiamen, 361005, China
| | - Siyuan Wang
- Department of Radiology, Xiang'an Hospital of Xiamen University, Xiamen, 361005, China
| | - Guangsong Wang
- Department of Radiology, Xiang'an Hospital of Xiamen University, Xiamen, 361005, China
| | - Ke Ren
- Department of Radiology, Xiang'an Hospital of Xiamen University, Xiamen, 361005, China. .,Xiamen Key Laboratory of Endocrine-Related Cancer Precision Medicine, Xiamen, China.
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Quantitative 3-tesla multiparametric MRI in differentiation between renal cell carcinoma subtypes. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2021. [DOI: 10.1186/s43055-020-00405-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
MRI provides several distinct quantitative parameters that may better differentiate renal cell carcinoma (RCC) subtypes. The purpose of the study is to evaluate the diagnostic accuracy of apparent diffusion coefficient (ADC), chemical shift signal intensity index (SII), and contrast enhancement in differentiation between different subtypes of renal cell carcinoma.
Results
There were 63 RCC as regard surgical histopathological analysis: 43 clear cell (ccRCC), 12 papillary (pRCC), and 8 chromophobe (cbRCC). The mean ADC ratio for ccRCC (0.75 ± 0.13) was significantly higher than that of pRCC (0.46 ± 0.12, P < 0.001) and cbRCC (0.41 ± 0.15, P < 0.001). The mean ADC value for ccRCC (1.56 ± 0.27 × 10−3 mm2/s) was significantly higher than that of pRCC (0.96 ± 0.25 × 10−3 mm2/s, P < 0.001) and cbRCC (0.89 ± 0.29 × 10−3 mm2/s, P < 0.001). The mean SII of pRCC (1.49 ± 0.04) was significantly higher than that of ccRCC (0.93 ± 0.01, P < 0.001) and cbRCC (1.01 ± 0.16, P < 0.001). The ccRCC absolute corticomedullary enhancement (196.7 ± 81.6) was significantly greater than that of cbRCC (177.8 ± 77.7, P < 0.001) and pRCC (164.3 ± 84.6, P < 0.001).
Conclusion
Our study demonstrated that multiparametric MRI is able to afford some quantitative features such as ADC ratio, SII, and absolute corticomedullary enhancement which can be used to accurately distinguish different subtypes of renal cell carcinoma.
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Tsili AC, Moulopoulos LA, Varakarakis IΜ, Argyropoulou MI. Cross-sectional imaging assessment of renal masses with emphasis on MRI. Acta Radiol 2021; 63:1570-1587. [PMID: 34709096 DOI: 10.1177/02841851211052999] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Magnetic resonance imaging (MRI) is a useful complementary imaging tool for the diagnosis and characterization of renal masses, as it provides both morphologic and functional information. A core MRI protocol for renal imaging should include a T1-weighted sequence with in- and opposed-phase images (or, alternatively with DIXON technique), T2-weighted and diffusion-weighted images as well as a dynamic contrast-enhanced sequence with subtraction images, followed by a delayed post-contrast T1-weighted sequence. The main advantages of MRI over computed tomography include increased sensitivity for contrast enhancement, less sensitivity for detection of calcifications, absence of pseudoenhancement, and lack of radiation exposure. MRI may be applied for renal cystic lesion characterization, differentiation of renal cell carcinoma (RCC) from benign solid renal tumors, RCC histologic grading, staging, post-treatment follow-up, and active surveillance of patients with treated or untreated RCC.
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Affiliation(s)
- Athina C Tsili
- Department of Clinical Radiology, School of Medicine, University of Ioannina, Ioannina, Greece
| | - Lia-Angela Moulopoulos
- 1st Department of Radiology, School of Medicine, National and Kapodistrian University of Athens, Areteion Hospital, Athens, Greece
| | - Ioannis Μ Varakarakis
- 2nd Department of Urology, National and Kapodistrian University of Athens, Sismanoglio Hospital, Athens, Greece
| | - Maria I Argyropoulou
- Department of Clinical Radiology, School of Medicine, University of Ioannina, Ioannina, Greece
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Barr RG, Wilson SR, Lyshchik A, McCarville B, Darge K, Grant E, Robbin M, Wilmann JK, Chong WK, Fleischer A, Paltiel HJ. Contrast -Enhanced Ultrasound: State of the Art in North America. Ultrasound Q 2021; 36:206-217. [PMID: 32890323 DOI: 10.1097/ruq.0000000000000514] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
The Society of Radiologists in Ultrasound convened a panel of specialists in contrast-enhanced ultrasound (CEUS) to produce a white paper on noncardiac CEUS in North America. The panel met in Chicago, Illinois, on October 24 and 25, 2017. The recommendations are based on analysis of current literature and common practice strategies and are thought to represent a reasonable approach to introduce the advantages of this safe and noninvasive technique for the benefit of our patients. Characterization of liver nodules, and pediatric vascular and intravesicular applications comprise the approved indications for CEUS in the United States. They, along with the very successful off-label use of CEUS for the kidney, are included in this publication.Other off-label uses are presented with emphasis on their value and literature support in the online version.
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Affiliation(s)
| | | | | | | | - Kassa Darge
- Children's Hospital of Philadelphia, Philadelphia, PA
| | - Edward Grant
- University of Southern California, Los Angeles, CA
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11
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Manganaro L, Nicolino GM, Dolciami M, Martorana F, Stathis A, Colombo I, Rizzo S. Radiomics in cervical and endometrial cancer. Br J Radiol 2021; 94:20201314. [PMID: 34233456 PMCID: PMC9327743 DOI: 10.1259/bjr.20201314] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
Radiomics is an emerging field of research that aims to find associations between quantitative information extracted from imaging examinations and clinical data to support the best clinical decision. In the last few years, some papers have been evaluating the role of radiomics in gynecological malignancies, mainly focusing on ovarian cancer. Nonetheless, cervical cancer is the most frequent gynecological malignancy in developing countries and endometrial cancer is the most common in western countries. The purpose of this narrative review is to give an overview of the latest published papers evaluating the role of radiomics in cervical and endometrial cancer, mostly evaluating association with tumor prognostic factors, with response to therapy and with prediction of recurrence and distant metastasis.
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Affiliation(s)
- Lucia Manganaro
- Department of Radiological, Oncological and Pathological Sciences; University of Rome Sapienza (IT), Rome, Italy
| | - Gabriele Maria Nicolino
- Post-graduate School in Radiodiagnostics, Università degli Studi di Milano, Via Festa del Perdono 7, Milan, Italy
| | - Miriam Dolciami
- Department of Radiological, Oncological and Pathological Sciences; University of Rome Sapienza (IT), Rome, Italy
| | - Federica Martorana
- Oncology Institute of Southern Switzerland, San Giovanni Hospital, 6500 Bellinzona, (CH), Switzerland
| | - Anastasios Stathis
- Oncology Institute of Southern Switzerland, San Giovanni Hospital, 6500 Bellinzona, (CH), Switzerland.,Facoltà di Scienze biomediche, Università della Svizzera italiana (USI), Via Buffi 13, 6900, Lugano (CH), Switzerland
| | - Ilaria Colombo
- Oncology Institute of Southern Switzerland, San Giovanni Hospital, 6500 Bellinzona, (CH), Switzerland
| | - Stefania Rizzo
- Facoltà di Scienze biomediche, Università della Svizzera italiana (USI), Via Buffi 13, 6900, Lugano (CH), Switzerland.,Istituto di Imaging della Svizzera Italiana (IIMSI), Ente Ospedaliero Cantonale, Via Tesserete 46, Lugano (CH), Switzerland
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12
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Radiomics models based on enhanced computed tomography to distinguish clear cell from non-clear cell renal cell carcinomas. Sci Rep 2021; 11:13729. [PMID: 34215760 PMCID: PMC8253856 DOI: 10.1038/s41598-021-93069-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Accepted: 06/17/2021] [Indexed: 12/17/2022] Open
Abstract
This study was to assess the effect of the predictive model for distinguishing clear cell RCC (ccRCC) from non-clear cell RCC (non-ccRCC) by establishing predictive radiomic models based on enhanced-computed tomography (CT) images of renal cell carcinoma (RCC). A total of 190 cases with RCC confirmed by pathology were retrospectively analyzed, with the patients being randomly divided into two groups, including the training set and testing set according to the ratio of 7:3. A total of 396 radiomic features were computationally obtained and analyzed with the Correlation between features, Univariate Logistics and Multivariate Logistics. Finally, 4 features were selected, and three machine models (Random Forest (RF), Support Vector Machine (SVM) and Logistic Regression (LR)) were established to discriminate RCC subtypes. The radiomics performance was compared with that of radiologist diagnosis. In the testing set, the RF model had an area under the curve (AUC) value of 0.909, a sensitivity of 0.956, and a specificity of 0.538. The SVM model had an AUC value of 0.841, a sensitivity of 1.0, and a specificity of 0.231, in the testing set. The LR model had an AUC value of 0.906, a sensitivity of 0.956, and a specificity of 0.692, in the testing set. The sensitivity and specificity of radiologist diagnosis to differentiate ccRCC from non-ccRCC were 0.850 and 0.581, respectively, with the AUC value of the radiologist diagnosis as 0.69. In conclusion, radiomics models based on CT imaging data show promise for augmenting radiological diagnosis in renal cancer, especially for differentiating ccRCC from non-ccRCC.
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Chen M, Yin F, Yu Y, Zhang H, Wen G. CT-based multi-phase Radiomic models for differentiating clear cell renal cell carcinoma. Cancer Imaging 2021; 21:42. [PMID: 34162442 PMCID: PMC8220848 DOI: 10.1186/s40644-021-00412-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Accepted: 06/09/2021] [Indexed: 01/08/2023] Open
Abstract
Background The aim of the study is to compare the diagnostic value of models that based on a set of CT texture and non-texture features for differentiating clear cell renal cell carcinomas(ccRCCs) from non-clear cell renal cell carcinomas(non-ccRCCs). Methods A total of 197 pathologically proven renal tumors were divided into ccRCC(n = 143) and non-ccRCC (n = 54) groups. The 43 non-texture features and 296 texture features that extracted from the 3D volume tumor tissue were assessed for each tumor at both Non-contrast Phase, NCP; Corticomedullary Phase, CMP; Nephrographic Phase, NP and Excretory Phase, EP. Texture-score were calculated by the Least Absolute Shrinkage and Selection Operator (LASSO) to screen the most valuable texture features. Model 1 contains the three most distinctive non-texture features with p < 0.001, Model 2 contains texture scores, and Model 3 contains the above two types of features. Results The three models shown good discrimination of the ccRCC from non-ccRCC in NCP, CMP, NP, and EP. The area under receiver operating characteristic curve (AUC)values of the Model 1, Model 2, and Model 3 in differentiating the two groups were 0.748–0.823, 0.776–0.887 and 0.864–0.900, respectively. The difference in AUC between every two of the three Models was statistically significant (p < 0.001). Conclusions The predictive efficacy of ccRCC was significantly improved by combining non-texture features and texture features to construct a combined diagnostic model, which could provide a reliable basis for clinical treatment options.
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Affiliation(s)
- Menglin Chen
- Medical Imaging teaching and research office, Nanfang hospital, Southern Medical University, No.1838 Guangzhoudadao Avenue north, Guangzhou, 510515, Guangdong, China.,Radiology department, The second affiliated hospital of Kunming medical university, No. 374 Dianmian Road, Kunming, 650032, Yunnan, China
| | - Fu Yin
- College of Electronics and Information Engineering, Shenzhen University, Shenzhen, 518068, China
| | - Yuanmeng Yu
- Department of MRI, The First People's Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology, No. 157 Jinbi Road, Kunming, 650032, Yunnan, China
| | - Haijie Zhang
- Department of Radiology, Shenzhen Second People's Hospital, No.3002, West Sungang Road, Futian District, Shenzhen, 518052, China.
| | - Ge Wen
- Medical Imaging teaching and research office, Nanfang hospital, Southern Medical University, No.1838 Guangzhoudadao Avenue north, Guangzhou, 510515, Guangdong, China.
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Tsili AC, Andriotis E, Gkeli MG, Krokidis M, Stasinopoulou M, Varkarakis IM, Moulopoulos LA. The role of imaging in the management of renal masses. Eur J Radiol 2021; 141:109777. [PMID: 34020173 DOI: 10.1016/j.ejrad.2021.109777] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 05/09/2021] [Accepted: 05/14/2021] [Indexed: 12/26/2022]
Abstract
The wide availability of cross-sectional imaging is responsible for the increased detection of small, usually asymptomatic renal masses. More than 50 % of renal cell carcinomas (RCCs) represent incidental findings on noninvasive imaging. Multimodality imaging, including conventional US, contrast-enhanced US (CEUS), CT and multiparametric MRI (mpMRI) is pivotal in diagnosing and characterizing a renal mass, but also provides information regarding its prognosis, therapeutic management, and follow-up. In this review, imaging data for renal masses that urologists need for accurate treatment planning will be discussed. The role of US, CEUS, CT and mpMRI in the detection and characterization of renal masses, RCC staging and follow-up of surgically treated or untreated localized RCC will be presented. The role of percutaneous image-guided ablation in the management of RCC will be also reviewed.
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Affiliation(s)
- Athina C Tsili
- Department of Clinical Radiology, School of Health Sciences, Faculty of Medicine, University of Ioannina, 45110, Ioannina, Greece.
| | - Efthimios Andriotis
- Department of Newer Imaging Methods of Tomography, General Anti-Cancer Hospital Agios Savvas, 11522, Athens, Greece.
| | - Myrsini G Gkeli
- 1st Department of Radiology, General Anti-Cancer Hospital Agios Savvas, 11522, Athens, Greece.
| | - Miltiadis Krokidis
- 1st Department of Radiology, School of Medicine, National and Kapodistrian University of Athens, Areteion Hospital, 11528, Athens, Greece; Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital Bern University Hospital, University of Bern, 3010, Bern, Switzerland.
| | - Myrsini Stasinopoulou
- Department of Newer Imaging Methods of Tomography, General Anti-Cancer Hospital Agios Savvas, 11522, Athens, Greece.
| | - Ioannis M Varkarakis
- 2nd Department of Urology, National and Kapodistrian University of Athens, Sismanoglio Hospital, 15126, Athens, Greece.
| | - Lia-Angela Moulopoulos
- 1st Department of Radiology, School of Medicine, National and Kapodistrian University of Athens, Areteion Hospital, 11528, Athens, Greece.
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Yamamoto T, Gulanbar A, Hayashi K, Kohno A, Komai Y, Yonese J, Matsueda K, Inamura K. Is hypervascular papillary renal cell carcinoma present? Abdom Radiol (NY) 2021; 46:1687-1693. [PMID: 33047228 DOI: 10.1007/s00261-020-02809-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2020] [Revised: 09/21/2020] [Accepted: 09/30/2020] [Indexed: 11/25/2022]
Abstract
PURPOSE We aimed to investigate atypical papillary renal cell carcinoma (PRCC) presenting with early contrast enhancement and late washout and to investigate the correlation between the CT attenuation value of the corticomedullary phase (CMP) of contrast-enhanced CT in PRCCs and the endothelial cell counts of these tumors. METHODS Twenty-two patients with pathologically confirmed PRCC were enrolled in this study. PRCCs were categorized into 18 typical PRCCs and 4 atypical PRCCs. The CT attenuation value of the lesion in the CMP was measured in the maximal section of the tumor using the region of interest. Microvessel density (MVD) was evaluated as a histopathologic parameter using tissue specimens immunohistochemically stained with an anti-ERG antibody. The CT attenuation value and MVD were compared between atypical and typical PRCCs using the Mann-Whitney U test, where p < 0.05 was considered significant. The correlations between CT attenuation value and MVD were evaluated in all PRCCs using single linear regression analysis. RESULTS The mean CT attenuation value and the MVD were significantly higher in atypical than in typical PRCCs. Correlation analyses revealed a weak positive correlation between the CT attenuation value and MVD. CONCLUSIONS We confirmed several cases of atypical PRCC that present with early contrast enhancement, such as clear cell renal cell carcinoma. In addition, a positive correlation was found between the CT attenuation value in the CMP of PRCCs and the vascular endothelial cell count.
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Affiliation(s)
- Tatsuya Yamamoto
- Department of Diagnostic Radiology, The Cancer Institute Hospital of the Japanese Foundation for Cancer Research, 3-8-31 Ariake, Koto-ku, Tokyo, 135-8550, Japan.
| | - Amori Gulanbar
- Division of Pathology, The Cancer Institute, Japanese Foundation for Cancer Research, 3-8-31 Ariake, Koto-ku, Tokyo, 135-8550, Japan
| | - Kuniyoshi Hayashi
- Division of Biostatistics and Bioinformatics, Graduate School of Public Health, St. Luke's International University, 3-6-2 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan
| | - Atsushi Kohno
- Department of Diagnostic Radiology, The Cancer Institute Hospital of the Japanese Foundation for Cancer Research, 3-8-31 Ariake, Koto-ku, Tokyo, 135-8550, Japan
| | - Yoshinobu Komai
- Department of Urology, The Cancer Institute Hospital of the Japanese Foundation for Cancer Research, 3-8-31 Ariake, Koto-ku, Tokyo, 135-8550, Japan
| | - Junji Yonese
- Department of Urology, The Cancer Institute Hospital of the Japanese Foundation for Cancer Research, 3-8-31 Ariake, Koto-ku, Tokyo, 135-8550, Japan
| | - Kiyoshi Matsueda
- Department of Diagnostic Radiology, The Cancer Institute Hospital of the Japanese Foundation for Cancer Research, 3-8-31 Ariake, Koto-ku, Tokyo, 135-8550, Japan
| | - Kentaro Inamura
- Division of Pathology, The Cancer Institute, Japanese Foundation for Cancer Research, 3-8-31 Ariake, Koto-ku, Tokyo, 135-8550, Japan
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Parmar N, Langdon J, Kaliannan K, Mathur M, Guo Y, Mahalingam S. Wunderlich Syndrome: Wonder What It Is. Curr Probl Diagn Radiol 2021; 51:270-281. [PMID: 33483188 DOI: 10.1067/j.cpradiol.2020.12.002] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Accepted: 12/31/2020] [Indexed: 12/23/2022]
Abstract
Wunderlich syndrome (WS) refers to spontaneous renal or perinephric hemorrhage occurring in the absence of known trauma. WS is much less common than hemorrhage occurring after iatrogenic or traumatic conditions. Lenk's triad of acute onset flank pain, flank mass, and hypovolemic shock is a classic presentation of WS but seen in less than a quarter of patients. The majority of patients present only with isolated flank pain and often imaged with an unenhanced CT in the emergency department. The underlying etiology is varied with most cases attributed to neoplasms, vascular disease, cystic renal disease and anticoagulation induced; the etiology is often occult on the initial exam and further evaluation is necessary. Urologists are familiar with this unique entity but radiologists, who are more likely to be the first to diagnose WS, may not be familiar with the imaging work up and management options. In the last decade or so, there has been a conspicuous shift in the approach to WS and thus it will be worthwhile to revisit WS in detail. In our review, we will review the multimodality imaging approach to WS, describe optimal follow up and elaborate on management.
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Affiliation(s)
- Nishita Parmar
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT
| | - Jonathan Langdon
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT
| | - Krithica Kaliannan
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT; Section of Emergency Radiology, Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT
| | - Mahan Mathur
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT
| | - Yang Guo
- Department of Radiology, Brigham and Women's Hospital, Boston, MA
| | - Sowmya Mahalingam
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT.
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Wang ZJ, Nikolaidis P, Khatri G, Dogra VS, Ganeshan D, Goldfarb S, Gore JL, Gupta RT, Hartman RP, Heilbrun ME, Lyshchik A, Purysko AS, Savage SJ, Smith AD, Wolfman DJ, Wong-You-Cheong JJ, Lockhart ME. ACR Appropriateness Criteria® Indeterminate Renal Mass. J Am Coll Radiol 2020; 17:S415-S428. [PMID: 33153554 DOI: 10.1016/j.jacr.2020.09.010] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2020] [Accepted: 09/01/2020] [Indexed: 12/15/2022]
Abstract
Renal masses are increasingly detected in asymptomatic individuals as incidental findings. CT and MRI with intravenous contrast and a dedicated multiphase protocol are the mainstays of evaluation for indeterminate renal masses. A single-phase postcontrast dual-energy CT can be useful when a dedicated multiphase renal protocol CT is not available. Contrast-enhanced ultrasound with microbubble agents is a useful alternative for characterizing renal masses, especially for patients in whom iodinated CT contrast or gadolinium-based MRI contrast is contraindicated. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.
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Affiliation(s)
- Zhen J Wang
- University of California San Francisco School of Medicine, San Francisco, California.
| | | | - Gaurav Khatri
- Panel Vice-Chair, UT Southwestern Medical Center, Dallas, Texas
| | - Vikram S Dogra
- University of Rochester Medical Center, Rochester, New York
| | | | - Stanley Goldfarb
- University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania; American Society of Nephrology
| | - John L Gore
- University of Washington, Seattle, Washington; American Urological Association
| | - Rajan T Gupta
- Duke University Medical Center, Durham, North Carolina
| | | | | | - Andrej Lyshchik
- Thomas Jefferson University Hospital, Philadelphia, Pennsylvania
| | | | - Stephen J Savage
- Medical University of South Carolina, Charleston, South Carolina; American Urological Association
| | - Andrew D Smith
- University of Alabama at Birmingham, Birmingham, Alabama
| | - Darcy J Wolfman
- Johns Hopkins University School of Medicine, Washington, District of Columbia
| | | | - Mark E Lockhart
- Specialty Chair, University of Alabama at Birmingham, Birmingham, Alabama
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Lopes Vendrami C, McCarthy RJ, Villavicencio CP, Miller FH. Predicting common solid renal tumors using machine learning models of classification of radiologist-assessed magnetic resonance characteristics. Abdom Radiol (NY) 2020; 45:2797-2809. [PMID: 32666233 DOI: 10.1007/s00261-020-02637-w] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Revised: 06/23/2020] [Accepted: 07/04/2020] [Indexed: 02/06/2023]
Abstract
PURPOSE Solid renal masses (SRM) are difficult to differentiate based on standard MR features. The purpose of this study was to assess MR imaging features of SRM to evaluate performance of ensemble methods of classifying SRM subtypes. MATERIALS AND METHODS MR images of SRM (n = 330) were retrospectively evaluated for standard and multiparametric (mp) features. Models of MR features for predicting malignant and benign lesions as well as subtyping SRM were developed using a training dataset and performance was evaluated in a test data-set using recursive partitioning (RP), gradient booting machine (GBM), and random forest (RF) methods. RESULTS In the test dataset, GBM and RF models demonstrated an accuracy of 86% (95% CI 75% to 93%) for predicting benign versus malignant SRM compared to 83% (95% CI 71% to 91%) for the RP model. RF had the greatest accuracy in predicting SRM subtypes, 81.2% (95% CI 69.5% to 89.9%) compared with GBM 73.4% (95% CI 60.9% to 83.7%) or RP 70.3% (95% CI 57.6% to 81.1%). Marginal homogeneity was reduced by the RF model compared with the RP model (P < 0.001), but not the GBM model (P = 0.135). All models had high sensitivity and specificity for clear cell and papillary renal cell carcinomas (RCC), but performed less well in differentiating chromophobe RCC, oncocytomas, and fat-poor angiomyolipomas. CONCLUSION Ensemble methods for prediction of SRM from radiologist-assessed image characteristics have high accuracy for distinguishing benign and malignant lesions. SRM subtype classification is limited by the ability to categorize chromophobe RCCs, oncocytomas, and fat-poor angiomyolipomas.
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Affiliation(s)
- Camila Lopes Vendrami
- Department of Radiology, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, 676 N. St. Clair St. Suite 800, Chicago, IL, 60611, USA
| | - Robert J McCarthy
- Department of Anesthesiology, Rush University, Chicago, IL, 60612, USA
| | - Carolina Parada Villavicencio
- Department of Radiology, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, 676 N. St. Clair St. Suite 800, Chicago, IL, 60611, USA
| | - Frank H Miller
- Department of Radiology, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, 676 N. St. Clair St. Suite 800, Chicago, IL, 60611, USA.
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Prospective performance of clear cell likelihood scores (ccLS) in renal masses evaluated with multiparametric magnetic resonance imaging. Eur Radiol 2020; 31:314-324. [PMID: 32770377 DOI: 10.1007/s00330-020-07093-0] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2020] [Revised: 06/02/2020] [Accepted: 07/20/2020] [Indexed: 12/12/2022]
Abstract
OBJECTIVES Solid renal masses have unknown malignant potential with commonly utilized imaging. Biopsy can offer a diagnosis of cancer but has a high non-diagnostic rate and complications. Reported use of multiparametric magnetic resonance imaging (mpMRI) to diagnose aggressive histology (i.e., clear cell renal cell carcinoma (ccRCC)) via a clear cell likelihood score (ccLS) was based on retrospective review of cT1a tumors. We aim to retrospectively assess the diagnostic performance of ccLS prospectively assigned to renal masses of all stages evaluated with mpMRI prior to histopathologic evaluation. METHODS In this retrospective cohort study from June 2016 to November 2019, 434 patients with 454 renal masses from 2 institutions with heterogenous patient populations underwent mpMRI with prospective ccLS assignment and had pathologic diagnosis. ccLS performance was assessed by contingency table analysis. The association between ccLS and ccRCC was assessed with logistic regression. RESULTS Mean age and tumor size were 60 ± 13 years and 5.4 ± 3.8 cm. Characteristics were similar between institutions except for patient age and race (both p < 0.001) and lesion laterality and histology (both p = 0.04). The PPV of ccLS increased with each increment in ccLS (ccLS1 5% [3/55], ccLS2 6% [3/47], ccLS3 35% [20/57], ccLS4 78% [85/109], ccLS5 93% [173/186]). Pooled analysis for ccRCC diagnosis revealed sensitivity 91% (258/284), PPV 87% (258/295) for ccLS ≥ 4, and specificity 56% (96/170), NPV 94% (96/102) for ccLS ≤ 2. Diagnostic performance was similar between institutions. CONCLUSIONS We confirm the optimal diagnostic performance of mpMRI to identify ccRCC in all clinical stages. High PPV and NPV of ccLS can help inform clinical management decision-making. KEY POINTS • The positive predictive value of the clear cell likelihood score (ccLS) for detecting clear cell renal cell carcinoma was 5% (ccLS1), 6% (ccLS2), 35% (ccLS3), 78% (ccLS4), and 93% (ccLS5). Sensitivity of ccLS ≥ 4 and specificity of ccLS ≤ 2 were 91% and 56%, respectively. • When controlling for confounding variables, ccLS is an independent risk factor for identifying clear cell renal cell carcinoma. • Utilization of the ccLS can help guide clinical care, including the decision for renal mass biopsy, reducing the morbidity and risk to patients.
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Diagnostic test accuracy of ADC values for identification of clear cell renal cell carcinoma: systematic review and meta-analysis. Eur Radiol 2020; 30:4023-4038. [PMID: 32144458 DOI: 10.1007/s00330-020-06740-w] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2019] [Revised: 01/14/2020] [Accepted: 02/11/2020] [Indexed: 12/11/2022]
Abstract
OBJECTIVES To perform a systematic review on apparent diffusion coefficient (ADC) values of renal tumor subtypes and meta-analysis on the diagnostic performance of ADC for differentiation of localized clear cell renal cell carcinoma (ccRCC) from other renal tumor types. METHODS Medline, Embase, and the Cochrane Library databases were searched for studies published until May 1, 2019, that reported ADC values of renal tumors. Methodological quality was evaluated. For the meta-analysis on diagnostic test accuracy of ADC for differentiation of ccRCC from other renal lesions, we applied a bivariate random-effects model and compared two subgroups of ADC measurement with vs. without cystic and necrotic areas. RESULTS We included 48 studies (2588 lesions) in the systematic review and 13 studies (1126 lesions) in the meta-analysis. There was no significant difference in ADC of renal parenchyma using b values of 0-800 vs. 0-1000 (p = 0.08). ADC measured on selected portions (sADC) excluding cystic and necrotic areas differed significantly from whole-lesion ADC (wADC) (p = 0.002). Compared to ccRCC, minimal-fat angiomyolipoma, papillary RCC, and chromophobe RCC showed significantly lower sADC while oncocytoma exhibited higher sADC. Summary estimates of sensitivity and specificity to differentiate ccRCC from other tumors were 80% (95% CI, 0.76-0.88) and 78% (95% CI, 0.64-0.89), respectively, for sADC and 77% (95% CI, 0.59-0.90) and 77% (95% CI, 0.69-0.86) for wADC. sADC offered a higher area under the receiver operating characteristic curve than wADC (0.852 vs. 0.785, p = 0.02). CONCLUSIONS ADC values of kidney tumors that exclude cystic or necrotic areas more accurately differentiate ccRCC from other renal tumor types than whole-lesion ADC values. KEY POINTS • Selective ADC of renal tumors, excluding cystic and necrotic areas, provides better discriminatory ability than whole-lesion ADC to differentiate clear cell RCC from other renal lesions, with area under the receiver operating characteristic curve (AUC) of 0.852 vs. 0.785, respectively (p = 0.02). • Selective ADC of renal masses provides moderate sensitivity and specificity of 80% and 78%, respectively, for differentiation of clear cell renal cell carcinoma (RCC) from papillary RCC, chromophobe RCC, oncocytoma, and minimal-fat angiomyolipoma. • Selective ADC excluding cystic and necrotic areas are preferable to whole-lesion ADC as an additional tool to multiphasic MRI to differentiate clear cell RCC from other renal lesions whether the highest b value is 800 or 1000.
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Does quantitative assessment of arterial phase hyperenhancement and washout improve LI-RADS v2018–based classification of liver lesions? Eur Radiol 2020; 30:2922-2933. [DOI: 10.1007/s00330-019-06596-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2019] [Revised: 11/08/2019] [Accepted: 11/18/2019] [Indexed: 12/18/2022]
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Rouvière O, Cornelis F, Brunelle S, Roy C, André M, Bellin MF, Boulay I, Eiss D, Girouin N, Grenier N, Hélénon O, Lapray JF, Lefèvre A, Matillon X, Ménager JM, Millet I, Ronze S, Sanzalone T, Tourniaire J, Rocher L, Renard-Penna R. Imaging protocols for renal multiparametric MRI and MR urography: results of a consensus conference from the French Society of Genitourinary Imaging. Eur Radiol 2020; 30:2103-2114. [PMID: 31900706 DOI: 10.1007/s00330-019-06530-z] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2019] [Revised: 09/19/2019] [Accepted: 10/18/2019] [Indexed: 12/23/2022]
Abstract
OBJECTIVES To develop technical guidelines for magnetic resonance imaging aimed at characterising renal masses (multiparametric magnetic resonance imaging, mpMRI) and at imaging the bladder and upper urinary tract (magnetic resonance urography, MRU). METHODS The French Society of Genitourinary Imaging organised a Delphi consensus conference with a two-round Delphi survey followed by a face-to-face meeting. Two separate questionnaires were issued for renal mpMRI and for MRU. Consensus was strictly defined using a priori criteria. RESULTS Forty-two expert uroradiologists completed both survey rounds with no attrition between the rounds. Fifty-six of 84 (67%) statements of the mpMRI questionnaire and 44/71 (62%) statements of the MRU questionnaire reached final consensus. For mpMRI, there was consensus that no injection of furosemide was needed and that the imaging protocol should include T2-weighted imaging, dual chemical shift imaging, diffusion-weighted imaging (use of multiple b-values; maximal b-value, 1000 s/mm2) and fat-saturated single-bolus multiphase (unenhanced, corticomedullary, nephrographic) contrast-enhanced imaging; late imaging (more than 10 min after injection) was judged optional. For MRU, the patients should void their bladder before the examination. The protocol must include T2-weighted imaging, anatomical fast T1/T2-weighted imaging, diffusion-weighted imaging (use of multiple b-values; maximal b-value, 1000 s/mm2) and fat-saturated single-bolus multiphase (unenhanced, corticomedullary, nephrographic, excretory) contrast-enhanced imaging. An intravenous injection of furosemide is mandatory before the injection of contrast medium. Heavily T2-weighted cholangiopancreatography-like imaging was judged optional. CONCLUSION This expert-based consensus conference provides recommendations to standardise magnetic resonance imaging of kidneys, ureter and bladder. KEY POINTS • Multiparametric magnetic resonance imaging (mpMRI) aims at characterising renal masses; magnetic resonance urography (MRU) aims at imaging the urinary bladder and the collecting systems. • For mpMRI, no injection of furosemide is needed. • For MRU, an intravenous injection of furosemide is mandatory before the injection of contrast medium; heavily T2-weighted cholangiopancreatography-like imaging is optional.
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Affiliation(s)
- Olivier Rouvière
- Department of Urinary and Vascular Imaging, Hôpital Edouard Herriot, Hospices Civils de Lyon, 5, place d'Arsonval, 69347, Lyon, France.
- Faculté de médecine Lyon Est, Université de Lyon, Université Lyon 1, Lyon, France.
| | - François Cornelis
- Department of Radiology, Hôpital Tenon, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Serge Brunelle
- Department of Radiology, Institut Paoli-Calmettes, Marseille, France
| | - Catherine Roy
- Department of Radiology B, CHU de Strasbourg, Nouvel Hôpital Civil, Strasbourg, France
| | - Marc André
- Department of Radiology, Hôpital Européen, Marseille, France
| | - Marie-France Bellin
- Department of Diagnostic and Interventional Radiology, Groupe Hospitalier Paris Sud, Assistance Publique-Hôpitaux de Paris, Le Kremlin Bicêtre, France
- Université Paris Sud, Le Kremlin Bicêtre, France
- IR4M, UMR 8081, Service hospitalier Joliot Curie, Orsay, France
| | - Isabelle Boulay
- Department of Radiology, Fondation Hôpital Saint Joseph, Paris, France
| | - David Eiss
- Department of Adult Radiology, Hôpital Necker-Enfants Malades, Assistance Publique-Hôpitaux de Paris, Paris, France
- Paris Descartes University, Sorbonne Paris Cité, Paris, France
| | | | - Nicolas Grenier
- Department of Diagnostic and Interventional Adult Imaging, CHU de Bordeaux, Bordeaux, France
- Université de Bordeaux, Bordeaux, France
| | - Olivier Hélénon
- Department of Adult Radiology, Hôpital Necker-Enfants Malades, Assistance Publique-Hôpitaux de Paris, Paris, France
- Paris Descartes University, Sorbonne Paris Cité, Paris, France
| | | | - Arnaud Lefèvre
- Centre d'Imagerie Médicale Tourville, Paris, France
- Department of Radiology, American Hospital of Paris, Neuilly, France
| | - Xavier Matillon
- Faculté de médecine Lyon Est, Université de Lyon, Université Lyon 1, Lyon, France
- Department of Urology and Transplantation, Hôpital Edouard Herriot, Hospices Civils de Lyon, Lyon, France
- CarMeN Laboratory, INSERM U1060, Lyon, France
| | | | - Ingrid Millet
- Department of Radiology, Hôpital Lapeyronie, Montpellier, France
- Université de Montpellier, Montpellier, France
| | - Sébastien Ronze
- Imagerie médicale Val d'Ouest Charcot (IMVOC), Ecully, France
| | - Thomas Sanzalone
- Department of Radiology, Centre Hospitalier de Valence, Valence, France
| | - Jean Tourniaire
- Department of Radiology, Clinique Rhône Durance, Avignon, France
| | - Laurence Rocher
- Department of Diagnostic and Interventional Radiology, Groupe Hospitalier Paris Sud, Assistance Publique-Hôpitaux de Paris, Le Kremlin Bicêtre, France
- Université Paris Sud, Le Kremlin Bicêtre, France
- IR4M, UMR 8081, Service hospitalier Joliot Curie, Orsay, France
| | - Raphaële Renard-Penna
- Academic Department of Radiology, Hôpital Pitié-Salpêtrière and Hôpital Tenon, Assistance Publique-Hôpitaux de Paris, Paris, France
- Sorbonne Universités, GRC no 5, ONCOTYPE-URO, Paris, France
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Diagnostic Imaging in Renal Tumors. KIDNEY CANCER 2020. [DOI: 10.1007/978-3-030-28333-9_17] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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25
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An overview of non-invasive imaging modalities for diagnosis of solid and cystic renal lesions. Med Biol Eng Comput 2019; 58:1-24. [DOI: 10.1007/s11517-019-02049-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2018] [Accepted: 09/17/2019] [Indexed: 12/22/2022]
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Johnson BA, Kim S, Steinberg RL, de Leon AD, Pedrosa I, Cadeddu JA. Diagnostic performance of prospectively assigned clear cell Likelihood scores (ccLS) in small renal masses at multiparametric magnetic resonance imaging. Urol Oncol 2019; 37:941-946. [PMID: 31540830 DOI: 10.1016/j.urolonc.2019.07.023] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2019] [Revised: 05/26/2019] [Accepted: 07/29/2019] [Indexed: 12/30/2022]
Abstract
INTRODUCTION Detection of small renal masses (SRM) is increasing with the use of cross-sectional imaging, although many incidental lesions have negligible metastatic potential. A method to identify this subtype would aid in risk stratification. A previously reported clear cell likelihood score (ccLS; 1-very unlikely, 2-unlikely, 3-equivocal, 4-likely, and 5-very likely), based on retrospective review of multiparametric magnetic resonance imaging (mpMRI), predicted the likelihood of encountering clear cell renal cell carcinoma (ccRCC) at surgery. Here, we assess the performance of ccLS prospectively assigned for prediction of ccRCC. METHODS Patients with a known renal mass who underwent mpMRI at a single institution between June 2016 and April 2018 were prospectively assigned a ccLS as part of the clinical MRI report. These patients were retrospectively reviewed, and those with a cT1a lesion and available pathological tissue diagnosis (diagnostic biopsy or extirpative surgery) were selected for analysis. RESULTS In total, 57 patients (mean age 61.7 ± 14.9 years) with 63 cT1a renal masses were identified. Mean tumor size was 2.7 ± 0.7 cm. Defining ccLS 4-5 lesions as positive demonstrated an overall accuracy of 84%, sensitivity of 89%, specificity of 79%, positive predictive value of 84%, and negative predictive value of 86%. A ccLS of 1-2 demonstrates an 86% accuracy and 100% sensitivity/positive predictive value of identifying non-ccRCC histology. CONCLUSIONS Utilizing prospectively assigned ccLS, we confirm that mpMRI can reasonably identify ccRCC histology in cT1a renal masses. Standardization of imaging protocols and reporting criteria such as the ccLS can be used to aid in the diagnosis and management of small renal masses.
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Affiliation(s)
- Brett A Johnson
- Department of Urology, University of Texas Southwestern, Dallas, TX
| | - Sandy Kim
- University of Texas Southwestern Medical School, Dallas, TX
| | - Ryan L Steinberg
- Department of Urology, University of Texas Southwestern, Dallas, TX
| | | | - Ivan Pedrosa
- Department of Urology, University of Texas Southwestern, Dallas, TX; Department of Radiology, University of Texas Southwestern, Dallas, TX; Advanced Imaging Research Center, University of Texas Southwestern, Dallas, TX
| | - Jeffrey A Cadeddu
- Department of Urology, University of Texas Southwestern, Dallas, TX; Department of Radiology, University of Texas Southwestern, Dallas, TX.
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Marcon J, Graser A, Horst D, Casuscelli J, Spek A, Stief CG, Reiser MF, Rübenthaler J, Buchner A, Staehler M. Papillary vs clear cell renal cell carcinoma. Differentiation and grading by iodine concentration using DECT—correlation with microvascular density. Eur Radiol 2019; 30:1-10. [DOI: 10.1007/s00330-019-06298-2] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2019] [Revised: 05/12/2019] [Accepted: 06/03/2019] [Indexed: 10/26/2022]
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28
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Li ZC, Zhai G, Zhang J, Wang Z, Liu G, Wu GY, Liang D, Zheng H. Differentiation of clear cell and non-clear cell renal cell carcinomas by all-relevant radiomics features from multiphase CT: a VHL mutation perspective. Eur Radiol 2018; 29:3996-4007. [DOI: 10.1007/s00330-018-5872-6] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2018] [Revised: 10/18/2018] [Accepted: 10/31/2018] [Indexed: 01/17/2023]
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29
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Schuster AH, Reimann N. [Biopsies of kidney lesions: when and how?]. Radiologe 2018; 58:906-913. [PMID: 30291407 DOI: 10.1007/s00117-018-0459-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
The demand for image-guided renal biopsy has increased due to the better detection of renal lesions; however, despite modern imaging techniques many small renal tumors cannot be classified as benign because they cannot be differentiated from renal cell carcinoma. Ultrasound and computed tomography (CT)-guided kidney biopsy is a safe and accurate method in the diagnostics of renal lesions and can be helpful in the selection of new ablative and pharmaceutical forms of treatment and avoid unnecessary operations. This article describes the clinical indications for an image-guided biopsy and discusses factors which should be considered when performing a biopsy.
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Affiliation(s)
- A H Schuster
- Lehrabteilung der Universität Innsbruck, Abteilung Radiologie, University of Innsbruck and Medical University of Innsbruck, Landeskrankenhaus Bregenz, Akademisches Lehrkrankenhaus, Carl-Pedenz-Straße 2, 6900, Bregenz, Österreich.
| | - N Reimann
- Lehrabteilung der Universität Innsbruck, Abteilung Radiologie, University of Innsbruck and Medical University of Innsbruck, Landeskrankenhaus Bregenz, Akademisches Lehrkrankenhaus, Carl-Pedenz-Straße 2, 6900, Bregenz, Österreich
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30
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Li SR, Pui MH, Guo Y, Wang HJ, Guan J, Zhang XL, Pan WB. Efficacy of 3D VIBE Dixon fat quantification for differentiating clear-cell from non-clear-cell renal cell carcinoma. Clin Radiol 2018; 73:975-980. [PMID: 30055765 DOI: 10.1016/j.crad.2018.06.018] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2017] [Accepted: 06/27/2018] [Indexed: 12/27/2022]
Abstract
AIM To assess the efficacy of three-dimensional (3D) volumetric interpolated breath-hold examination (VIBE) magnetic resonance imaging (MRI) with Dixon quantification for differentiating clear-cell from non-clear-cell types of renal cell carcinoma (RCC). MATERIALS AND METHODS The 3D VIBE Dixon renal MRI examinations of 44 patients with 45 histologically confirmed RCCs was analysed. The fat fractions and signal intensity indexes (SIindex) of the solid portions of clear-cell and non-clear-cell RCCs were measured and compared using Student's t-test and receiver operating characteristic (ROC) curves. The agreement of measurements among observers was evaluated by the intraclass correlation coefficient (ICC), and Bland-Altman plots. RESULTS The mean values of fat fraction (13.16±7.16%) and SIindex (22.64±15.7%) in clear-cell RCCs were significantly higher than that in non-clear-cell RCCs (7.7±2% and 7.9±4.8%; p<0.001, respectively). With the area under the ROC curve (AUC) of the fat fraction at 0.811, 75% (95% CI: 55.1-89.43%) sensitivity and 76.5% (95% CI: 50.1-93.2%) specificity for diagnosing clear-cell RCC were obtained at a cut-off fat fraction value of 8.9%. With a cut-off value of 8.89%, the diagnostic sensitivity and specificity were 85.7% (95% CI: 67.3-96%) and 70.6% (95% CI: 44-89.7%), respectively. The AUC of the SIindex was 0.870 (0.766-0.973). ICC and Bland-Altman plots show excellent agreement of the tumour fat fraction and SIindex measurement between the two observers. CONCLUSION Intracellular lipid content analysis using the 3D Dixon technique can help to differentiate clear-cell from non-clear-cell RCCs.
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Affiliation(s)
- S-R Li
- Department of Radiology, The First Affiliated Hospital of Sun Yat-sen University, 58 Zhongshan Road 2, Guangzhou, Guangdong, People's Republic of China
| | - M H Pui
- Department of Radiology, Timmins District Hospital, 700 Ross Avenue E, Timmins, Ontario P4N 8P2, Canada
| | - Y Guo
- Department of Radiology, The First Affiliated Hospital of Sun Yat-sen University, 58 Zhongshan Road 2, Guangzhou, Guangdong, People's Republic of China.
| | - H-J Wang
- Department of Radiology, The First Affiliated Hospital of Sun Yat-sen University, 58 Zhongshan Road 2, Guangzhou, Guangdong, People's Republic of China
| | - J Guan
- Department of Radiology, The First Affiliated Hospital of Sun Yat-sen University, 58 Zhongshan Road 2, Guangzhou, Guangdong, People's Republic of China
| | - X-L Zhang
- Department of Radiology, The First Affiliated Hospital of Sun Yat-sen University, 58 Zhongshan Road 2, Guangzhou, Guangdong, People's Republic of China
| | - W-B Pan
- Department of Radiology, The First Affiliated Hospital of Sun Yat-sen University, 58 Zhongshan Road 2, Guangzhou, Guangdong, People's Republic of China
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Tricard T, Tsoumakidou G, Lindner V, Garnon J, Albrand G, Cathelineau X, Gangi A, Lang H. Thérapies ablatives dans le cancer du rein : indications. Prog Urol 2017; 27:926-951. [DOI: 10.1016/j.purol.2017.07.245] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2017] [Accepted: 07/22/2017] [Indexed: 12/19/2022]
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Lopes Vendrami C, Parada Villavicencio C, DeJulio TJ, Chatterjee A, Casalino DD, Horowitz JM, Oberlin DT, Yang GY, Nikolaidis P, Miller FH. Differentiation of Solid Renal Tumors with Multiparametric MR Imaging. Radiographics 2017; 37:2026-2042. [DOI: 10.1148/rg.2017170039] [Citation(s) in RCA: 60] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Affiliation(s)
- Camila Lopes Vendrami
- From the Departments of Radiology (C.L.V., C.P.V., A.C., D.D.C., J.M.H., P.N., F.H.M.), Pathology (T.J.D., G.Y.Y.), and Urology (D.T.O.), Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, 676 N St Clair St, Suite 800, Chicago, IL 60611
| | - Carolina Parada Villavicencio
- From the Departments of Radiology (C.L.V., C.P.V., A.C., D.D.C., J.M.H., P.N., F.H.M.), Pathology (T.J.D., G.Y.Y.), and Urology (D.T.O.), Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, 676 N St Clair St, Suite 800, Chicago, IL 60611
| | - Todd J. DeJulio
- From the Departments of Radiology (C.L.V., C.P.V., A.C., D.D.C., J.M.H., P.N., F.H.M.), Pathology (T.J.D., G.Y.Y.), and Urology (D.T.O.), Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, 676 N St Clair St, Suite 800, Chicago, IL 60611
| | - Argha Chatterjee
- From the Departments of Radiology (C.L.V., C.P.V., A.C., D.D.C., J.M.H., P.N., F.H.M.), Pathology (T.J.D., G.Y.Y.), and Urology (D.T.O.), Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, 676 N St Clair St, Suite 800, Chicago, IL 60611
| | - David D. Casalino
- From the Departments of Radiology (C.L.V., C.P.V., A.C., D.D.C., J.M.H., P.N., F.H.M.), Pathology (T.J.D., G.Y.Y.), and Urology (D.T.O.), Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, 676 N St Clair St, Suite 800, Chicago, IL 60611
| | - Jeanne M. Horowitz
- From the Departments of Radiology (C.L.V., C.P.V., A.C., D.D.C., J.M.H., P.N., F.H.M.), Pathology (T.J.D., G.Y.Y.), and Urology (D.T.O.), Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, 676 N St Clair St, Suite 800, Chicago, IL 60611
| | - Daniel T. Oberlin
- From the Departments of Radiology (C.L.V., C.P.V., A.C., D.D.C., J.M.H., P.N., F.H.M.), Pathology (T.J.D., G.Y.Y.), and Urology (D.T.O.), Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, 676 N St Clair St, Suite 800, Chicago, IL 60611
| | - Guang-Yu Yang
- From the Departments of Radiology (C.L.V., C.P.V., A.C., D.D.C., J.M.H., P.N., F.H.M.), Pathology (T.J.D., G.Y.Y.), and Urology (D.T.O.), Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, 676 N St Clair St, Suite 800, Chicago, IL 60611
| | - Paul Nikolaidis
- From the Departments of Radiology (C.L.V., C.P.V., A.C., D.D.C., J.M.H., P.N., F.H.M.), Pathology (T.J.D., G.Y.Y.), and Urology (D.T.O.), Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, 676 N St Clair St, Suite 800, Chicago, IL 60611
| | - Frank H. Miller
- From the Departments of Radiology (C.L.V., C.P.V., A.C., D.D.C., J.M.H., P.N., F.H.M.), Pathology (T.J.D., G.Y.Y.), and Urology (D.T.O.), Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, 676 N St Clair St, Suite 800, Chicago, IL 60611
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PET-MRI of the Pancreas and Kidneys. CURRENT RADIOLOGY REPORTS 2017. [DOI: 10.1007/s40134-017-0229-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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34
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Canvasser NE, Kay FU, Xi Y, Pinho DF, Costa D, de Leon AD, Khatri G, Leyendecker JR, Yokoo T, Lay A, Kavoussi N, Koseoglu E, Cadeddu JA, Pedrosa I. Diagnostic Accuracy of Multiparametric Magnetic Resonance Imaging to Identify Clear Cell Renal Cell Carcinoma in cT1a Renal Masses. J Urol 2017; 198:780-786. [PMID: 28457802 DOI: 10.1016/j.juro.2017.04.089] [Citation(s) in RCA: 78] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/18/2017] [Indexed: 01/13/2023]
Abstract
PURPOSE The detection of small renal masses is increasing with the use of cross-sectional imaging, although many incidental lesions have negligible metastatic potential. Among malignant masses clear cell renal cell carcinoma is the most prevalent and aggressive subtype. A method to identify such histology would aid in risk stratification. Our goal was to evaluate a likelihood scale for multiparametric magnetic resonance imaging in the diagnosis of clear cell histology. MATERIALS AND METHODS We retrospectively reviewed the records of patients with cT1a masses who underwent magnetic resonance imaging and partial or radical nephrectomy from December 2011 to July 2015. Seven radiologists with different levels of experience who were blinded to final pathology findings independently reviewed studies based on a predefined algorithm. They applied a clear cell likelihood score, including 1-definitely not, 2-probably not, 3-equivocal, 4-probably and 5-definitely. Binary classification was used to determine the accuracy of clear cell vs all other histologies. Interobserver agreement was calculated with the weighted κ statistic. RESULTS A total of 110 patients with 121 masses were identified. Mean tumor size was 2.4 cm and 50% of the lesions were clear cell. Defining clear cell as scores of 4 or greater demonstrated 78% sensitivity and 80% specificity while scores of 3 or greater showed 95% sensitivity and 58% specificity. Interobserver agreement was moderate to good with a mean κ of 0.53. CONCLUSIONS A clear cell likelihood score used with magnetic resonance imaging can reasonably identify clear cell histology in small renal masses and may decrease the number of diagnostic renal mass biopsies. Standardization of imaging protocols and reporting criteria is needed to improve interobserver reliability.
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Affiliation(s)
- Noah E Canvasser
- Department of Urology, University of Texas Southwestern, Dallas, Texas
| | - Fernando U Kay
- Department of Radiology, University of Texas Southwestern, Dallas, Texas
| | - Yin Xi
- Department of Radiology, University of Texas Southwestern, Dallas, Texas
| | - Daniella F Pinho
- Department of Radiology, University of Texas Southwestern, Dallas, Texas
| | - Daniel Costa
- Department of Radiology, University of Texas Southwestern, Dallas, Texas
| | | | - Gaurav Khatri
- Department of Radiology, University of Texas Southwestern, Dallas, Texas
| | - John R Leyendecker
- Department of Radiology, University of Texas Southwestern, Dallas, Texas
| | - Takeshi Yokoo
- Department of Radiology, University of Texas Southwestern, Dallas, Texas
| | - Aaron Lay
- Department of Urology, University of Texas Southwestern, Dallas, Texas
| | - Nicholas Kavoussi
- Department of Urology, University of Texas Southwestern, Dallas, Texas
| | - Ersin Koseoglu
- Department of Urology, University of Texas Southwestern, Dallas, Texas
| | - Jeffrey A Cadeddu
- Department of Urology, University of Texas Southwestern, Dallas, Texas; Department of Radiology, University of Texas Southwestern, Dallas, Texas.
| | - Ivan Pedrosa
- Department of Radiology, University of Texas Southwestern, Dallas, Texas; Imaging Research Center, University of Texas Southwestern, Dallas, Texas
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