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Wang K, Guo B, Yao Z, Li G. Clinical T1/2 renal cell carcinoma: multiparametric dynamic contrast-enhanced MRI features-based model for the prediction of individual adverse pathology. World J Surg Oncol 2024; 22:145. [PMID: 38822338 PMCID: PMC11143715 DOI: 10.1186/s12957-024-03431-4] [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: 03/15/2024] [Accepted: 05/27/2024] [Indexed: 06/02/2024] Open
Abstract
BACKGROUND The detection of renal cell carcinoma (RCC) has been rising due to the enhanced utilization of cross-sectional imaging and incidentally discovered lesions with adverse pathology demonstrate potential for metastasis. The purpose of our study was to determine the clinical and multiparametric dynamic contrast-enhanced magnetic resonance imaging (CEMRI) associated independent predictors of adverse pathology for cT1/2 RCC and develop the predictive model. METHODS We recruited 105 cT1/2 RCC patients between 2018 and 2022, all of whom underwent preoperative CEMRI and had complete clinicopathological data. Adverse pathology was defined as RCC patients with nuclear grade III-IV; pT3a upstage; type II papillary RCC, collecting duct or renal medullary carcinoma, unclassified RCC; sarcomatoid/rhabdoid features. The qualitative and quantitative CEMRI parameters were independently reviewed by two radiologists. Univariate and multivariate binary logistic regression analyses were utilized to determine the independent predictors of adverse pathology for cT1/2 RCC and construct the predictive model. The receiver operating characteristic (ROC) curve, confusion matrix, calibration plot, and decision curve analysis (DCA) were conducted to compare the diagnostic performance of different predictive models. The individual risk scores and linear predicted probabilities were calculated for risk stratification, and the Kaplan-Meier curve and log-rank tests were used for survival analysis. RESULTS Overall, 45 patients were pathologically confirmed as RCC with adverse pathology. Clinical characteristics, including gender, and CEMRI parameters, including RENAL score, tumor margin irregularity, necrosis, and tumor apparent diffusion coefficient (ADC) value were identified as independent predictors of adverse pathology for cT1/2 RCC. The clinical-CEMRI predictive model yielded an area under the curve (AUC) of the ROC curve of 0.907, which outperformed the clinical model or CEMRI signature model alone. Good calibration, better clinical usefulness, excellent risk stratification ability of adverse pathology and prognosis were also achieved for the clinical-CEMRI predictive model. CONCLUSIONS The proposed clinical-CEMRI predictive model offers the potential for preoperative prediction of adverse pathology for cT1/2 RCC. With the ability to forecast adverse pathology, the predictive model could significantly benefit patients and clinicians alike by providing enhanced guidance for treatment planning and decision-making.
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Affiliation(s)
- Keruo Wang
- Department of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, 300211, China
| | - Baoyin Guo
- Department of Urology, Tianjin Baodi Hospital, Baodi Clinical College of Tianjin Medical University, Tianjin, 301800, China
| | - Zhili Yao
- Department of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, 300211, China
| | - Gang Li
- Department of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, 300211, China.
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Pan L, Chen M, Sun J, Jin P, Ding J, Cai P, Chen J, Xing W. Prediction of Fuhrman grade of renal clear cell carcinoma by multimodal MRI radiomics: a retrospective study. Clin Radiol 2024; 79:e273-e281. [PMID: 38065776 DOI: 10.1016/j.crad.2023.11.006] [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: 07/05/2023] [Revised: 10/16/2023] [Accepted: 11/05/2023] [Indexed: 01/02/2024]
Abstract
AIM To explore the value of multimodal magnetic resonance imaging (MRI) radiomics combined with traditional radiologist-defined semantic characteristics and conventional (cMRI) and functional MRI (fMRI) texture features in predicting Fuhrman grade of clear cell renal cell carcinoma (ccRCC). MATERIALS AND METHODS The data of 89 patients with histopathologically proven ccRCC (low-grade, 54; high-grade, 35) were collected. Texture features were extracted from cMRI (T1- and T2-weighted imaging) and fMRI (Dixon-MRI; blood-oxygen-level dependent [BOLD]-MRI; and susceptibility-weighted imaging [SWI]) images, and the traditional characteristics (TC) were evaluated. Logistic regression analysis was performed to develop models based on TC, cMRI, and fMRI texture features for grading. Receiver operating characteristic (ROC) curve analysis and leave-group-out cross-validation (LGOCV) were performed to test the reliability of combined models. RESULTS Two T2-weighted imaging-based, two Dixon_W-based, one Dixon_F-based, one BOLD-based, and three SWI-based texture features, and three TC were extracted for feature selection. TC, cMRI, fMRI, cMRI+fMRI, cMRI+TC, fMRI+TC, and cMRI+fMRI+TC models were constructed. The AUC of the cMRI+fMRI+TC model for differentiating high- from low-grade ccRCC was 0.74, with 81.42% accuracy, 75.93% sensitivity, and 91.43% specificity. The fMRI+TC model exhibited a performance similar to that of the cMRI+fMRI+TC model (p>0.05). The areas under the curve (AUCs) of the fMRI+TC and cMRI+fMRI+TC models were significantly higher than those of the other five models (all p<0.05). For the cMRI+fMRI+TC model, the mean accuracy was 85.40% after 100 LGOCV for the test sets. CONCLUSION Multimodal MRI radiomics combined with TC, cMRI, and fMRI texture features may be a reliable quantitative approach for differentiating high-grade ccRCC from low-grade ccRCC.
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Affiliation(s)
- L Pan
- Department of Radiology, Third Affiliated Hospital of Soochow University, Changzhou 213003, Jiangsu, China
| | - M Chen
- Department of Radiology, Third Affiliated Hospital of Soochow University, Changzhou 213003, Jiangsu, China
| | - J Sun
- Department of Radiology, Third Affiliated Hospital of Soochow University, Changzhou 213003, Jiangsu, China
| | - P Jin
- Department of Public Health, Nanjing Medical University, Nanjing 211166, Jiangsu, China
| | - J Ding
- Department of Radiology, Third Affiliated Hospital of Soochow University, Changzhou 213003, Jiangsu, China
| | - P Cai
- Department of Radiology, Third Affiliated Hospital of Soochow University, Changzhou 213003, Jiangsu, China
| | - J Chen
- Department of Radiology, Third Affiliated Hospital of Soochow University, Changzhou 213003, Jiangsu, China.
| | - W Xing
- Department of Radiology, Third Affiliated Hospital of Soochow University, Changzhou 213003, Jiangsu, China.
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Shang W, Hong G, Li W. MRI for the detection of small malignant renal masses: a systematic review and meta-analysis. Front Oncol 2023; 13:1194128. [PMID: 37876965 PMCID: PMC10591109 DOI: 10.3389/fonc.2023.1194128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2023] [Accepted: 09/12/2023] [Indexed: 10/26/2023] Open
Abstract
Objective We aimed to review the available evidence on the diagnostic performance of magnetic resonance imaging in differentiating malignant from benign small renal masses. Methods An electronic literature search of Web of Science, MEDLINE (Ovid and PubMed), Cochrane Library, EMBASE, and Google Scholar was performed to identify relevant articles up to 31 January 2023. We included studies that reported the diagnostic accuracy of using magnetic resonance imaging to differentiate small (≤4 cm) malignant from benign renal masses. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were calculated using the bivariate model and the hierarchical summary receiver operating characteristic model. The study quality evaluation was performed with the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Results A total of 10 studies with 860 small renal masses (815 patients) were included in the current meta-analysis. The pooled sensitivity and specificity of the studies for the detection of malignant masses were 0.85 (95% CI 0.79-0.90) and 0.83 (95% CI 0.67-0.92), respectively. Conclusions MRI had a moderate diagnostic performance in differentiating small malignant renal masses from benign ones. Substantial heterogeneity was observed between studies for both sensitivity and specificity.
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Affiliation(s)
| | | | - Wei Li
- Department of Medical Imaging, Jiangsu Vocational College of Medicine, Yancheng, China
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4
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Huang W, Peng Y, Zhang Y, Qiu Y, Liu Y, Wang A, Kang L. Multimodality imaging of Xp11.2 translocation/TFE3 gene fusion associated with renal cell carcinoma: a case report. Front Med (Lausanne) 2023; 10:1266630. [PMID: 37795411 PMCID: PMC10546202 DOI: 10.3389/fmed.2023.1266630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Accepted: 08/31/2023] [Indexed: 10/06/2023] Open
Abstract
Background Xp11.2 translocation/TFE3 gene fusion associated with renal cell carcinoma (Xp11.2 RCC) exhibits unique biological characteristics and is associated with an increased incidence of tumor thrombosis, lymph node metastasis, and advanced disease stages. Multimodality imaging, including US, contrast-enhanced CT, multi-parametric MRI, and 18F-FDG PET/CT plays a crucial role in the preoperative diagnosis and differentiation of renal tumors. Case report A 15-year-old female presented with lumbar pain worsened, and developed persistent painless hematuria. The CT attenuation values of the scan without contrast, corticomedullary phase, nephrographic phase, and delayed phases were 35 HU, 83 HU, 82 HU, and 75 HU, respectively. The solid component of the mass displayed heterogeneous marked enhancement. Furthermore, MRU indicated that the lesion involved the cortical medulla and infringed on the renal sinus fat. The lesion appeared isosignal in T1WI, slightly low signal in T2WI, and slightly high signal in DWI. The degree of enhancement in the three phases of enhancement scan was lower than that in the renal parenchyma, and hemorrhage and necrosis were observed within the internal part of the lesion. To further clarify the staging, the patient underwent 18F-FDG PET/CT. PET/CT images showed multiple irregular occupancies in the right kidney with unclear borders, showing a heterogeneous increase in 18F-FDG uptake, with SUVmax values ranging from 2.3 to 5.2 in the routine imaging phase (60 min post-injection), compared to SUVmax values ranging from 2.8 to 6.9 in the delayed imaging phase (160 min post-injection). Additionally, multiple enlarged and fused lymph nodes were observed in the medial part of the right kidney and the retroperitoneum, exhibiting a heterogeneous increase in 18F-FDG uptake, with SUVmax values ranging from 4.1 to 8.7 in the routine imaging phase, compared to SUVmax values ranging from 4.4 to 9.1 in the delayed imaging phase. The postoperative pathology, immunohistochemistry, and molecular analysis of histiocytes were consistent with a diagnosis of Xp11.2 RCC. One month after surgery, enhanced-CT examination of the patient revealed lung metastasis, peritoneal metastasis, and multiple lymph node metastases throughout the body, with an overall survival of 16 months. Conclusion Xp11.2 RCC exhibits unique biological characteristics and is associated with an increased incidence of tumor thrombosis, lymph node metastasis, and advanced disease stages. Long-term follow-up is essential to monitor the likelihood of recurrence and metastasis. 18F-FDG PET/CT examination can comprehensively visualize the lesion's location and extent, providing a basis for clinical tumor staging and aiding in treatment monitoring and follow-up. To address the limitations of FDG, the utilization of specific tracers designed for RCC or tracers that are not excreted via the urinary system would be ideal. Further advancements in molecular imaging technologies and the development of novel tracers hold great promise in advancing the diagnosis and management of RCC, ultimately contributing to better patient outcomes and overall disease management.
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Affiliation(s)
- Wenpeng Huang
- Department of Nuclear Medicine, Peking University First Hospital, Beijing, China
| | - Yushuo Peng
- Department of Nuclear Medicine, Peking University First Hospital, Beijing, China
| | - Yongbai Zhang
- Department of Nuclear Medicine, Peking University First Hospital, Beijing, China
| | - Yongkang Qiu
- Department of Nuclear Medicine, Peking University First Hospital, Beijing, China
| | - Yi Liu
- Department of Urology, Peking University First Hospital, Beijing, China
- Institute of Urology, Peking University, Beijing, China
- National Urological Cancer Center, Beijing, China
| | - Aixiang Wang
- Department of Urology, Peking University First Hospital, Beijing, China
- Institute of Urology, Peking University, Beijing, China
- National Urological Cancer Center, Beijing, China
| | - Lei Kang
- Department of Nuclear Medicine, Peking University First Hospital, Beijing, China
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Shen L, Tse JR, Lemieux S, Yoon L, Mullane PC, Liang T, Davenport MS, Pedrosa I, Silverman SG. Risk of malignancy in T1-hyperintense Bosniak version 2019 class II and IIF cystic renal masses. Abdom Radiol (NY) 2023; 48:2636-2648. [PMID: 37202641 DOI: 10.1007/s00261-023-03955-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 05/04/2023] [Accepted: 05/04/2023] [Indexed: 05/20/2023]
Abstract
BACKGROUND Bosniak classification version 2019 includes cystic masses in class II and IIF based partly on their hyperintense appearance at T1-weighted MRI. The prevalence of malignancy in non-enhancing heterogeneously T1-hyperintense masses is unknown, nor whether the pattern of T1 hyperintensity affects malignancy likelihood. PURPOSE To determine the malignancy proportion among six patterns of T1 hyperintensity within non-enhancing cystic renal masses. METHODS This retrospective, single-institution study included 72 Bosniak class II and IIF, non-enhancing, T1-hyperintense cystic renal masses. Diagnosis was confirmed by histopathology or by follow-up imaging demonstrating 5-year size and morphologic stability, decreased in size by ≥ 30%, resolution, or Bosniak down-classification. Six patterns of T1 hyperintensity were pre-defined: homogeneous (pattern A), fluid-fluid level (pattern B), peripherally markedly T1-hyperintense (pattern C), containing a T1-hyperintense non-enhancing nodule (pattern D), peripherally T1-hypointense (pattern E), and heterogeneously T1-hyperintense without a distinct pattern (pattern F). Three readers independently assigned each mass to a pattern. Individual and mean malignancy proportion were determined. Mann-Whitney test and Fischer's exact test compared the likelihood of malignancy between patterns. Inter-reader agreement was analyzed with Gwet's agreement coefficient (AC). RESULTS Among 72 masses, the mean number of masses assigned was 11 (15%) to pattern A, 21 (29%) to pattern B, 6 (8%) to pattern C, 7 (10%) to pattern D, 5 (7%) to pattern E, and 22 (31%) to pattern F. Five of 72 masses (7%) were malignant; none was assigned pattern A, B, or D. Mean malignancy proportion was 5% (0/9, 1/6, and 0/4) for pattern C, 13% (0/4, 1/3, and 1/7) for pattern E, and 18% (5/20, 3/21, and 4/25) for pattern F. Malignant masses were more likely assigned to pattern E or F (p = 0.003-0.039). Inter-reader agreement was substantial (Gwet's AC: 0.68). CONCLUSION Bosniak version 2019 class IIF masses that are non-enhancing and heterogeneously T1-hyperintense with a fluid-fluid level are likely benign. Those that are non-enhancing and heterogeneously T1-hyperintense without a distinct pattern have a malignancy proportion up to 25% (5/20).
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Affiliation(s)
- Luyao Shen
- Department of Radiology, Stanford University School of Medicine, 300 Pasteur Drive, Stanford, CA, 94305, USA.
| | - Justin R Tse
- Department of Radiology, Stanford University School of Medicine, 300 Pasteur Drive, Stanford, CA, 94305, USA
| | - Simon Lemieux
- Department of Radiology, Stanford University School of Medicine, 300 Pasteur Drive, Stanford, CA, 94305, USA
| | - Luke Yoon
- Department of Radiology, Stanford University School of Medicine, 300 Pasteur Drive, Stanford, CA, 94305, USA
| | - Patrick C Mullane
- Department of Pathology, Stanford University School of Medicine, Lane Building, L235, 300 Pasteur Drive, Stanford, CA, 94305, USA
| | - Tie Liang
- Department of Radiology, Stanford University School of Medicine, 300 Pasteur Drive, Stanford, CA, 94305, USA
| | - Matthew S Davenport
- Department of Radiology and Urology, Michigan Medicine, University of Michigan, 1500 E Medical Center Dr, Ann Arbor, MI, B2-A209A48109, USA
| | - Ivan Pedrosa
- Department of Radiology, University of Texas Southwestern Medical Center, 2201 Inwood Rd. 2nd Floor, Suite 202, Dallas, TX, 75390, USA
| | - Stuart G Silverman
- Department of Radiology, Brigham and Women's Hospital, Harvard University, 75 Francis St., Boston, MA, 02115, USA
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Aydoğan C, Cansu A, Aydoğan Z, Erdemi S, Teymur A, Bektaş O, Mungan S, Kazaz İO. Diagnostic performance of multiparametric magnetic resonance imaging in the differentiation of clear cell renal cell cancer. Abdom Radiol (NY) 2023; 48:2349-2360. [PMID: 37071122 DOI: 10.1007/s00261-023-03882-5] [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: 12/03/2022] [Revised: 03/02/2023] [Accepted: 03/03/2023] [Indexed: 04/19/2023]
Abstract
PURPOSE This study aimed to evaluate the diagnostic performance of multiparametric magnetic resonance imaging (mpMRI) in the differentiation of renal cell carcinoma (RCC) subtypes. METHODS This is a retrospective diagnostic performance study, in which the diagnostic performances of mpMRI features were evaluated to differentiate clear cell RCC (ccRCC) from non-clear cell RCC (non-ccRCC). Adult patients who were evaluated using a 3-Tesla dynamic contrast-enhanced mpMRI before undergoing partial or radical nephrectomy for possible malignant renal tumors were included in the study. Signal intensity change percentages (SICP) between contrast-enhanced phases and pre-administration period for both the tumor and normal renal cortex, and tumor-to-cortex enhancement index (TCEI); tumor apparent diffusion coefficient (ADC) values; tumor-to-cortex ADC ratio; and a scale which was developed according to the tumor signal intensities on the axial fat-suppressed T2-weighted Half-Fourier Acquisition Single-shot Turbo spin Echo (HASTE) images were used in ROC analysis to estimate the presence of ccRCC in the patients. The reference test positivity was the histopathologic examination of the surgical specimens. RESULTS Ninety-eight tumors from 91 patients were included in the study, and 59 of them were ccRCC, 29 were pRCC, and 10 were chRCC. The mpMRI features that had the three highest sensitivity rates were excretory phase SICP, T2-weighted HASTE scale score, and corticomedullary phase TCEI (93.2%, 91.5%, and 86.4%, respectively). However, those with the three highest specificity rates were nephrographic phase TCEI, excretory phase TCEI, and tumor ADC value (94.9%, 94.9%, and 89.7%, respectively). CONCLUSION Several parameters on mpMRI showed an acceptable performance to differentiate ccRCC from non-ccRCC.
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Affiliation(s)
- Cemal Aydoğan
- Department of Radiology, Trabzon Ahi Evren Thoracic and Cardiovascular Surgery Training and Research Hospital, Trabzon, Turkey.
| | - Ayşegül Cansu
- Department of Radiology, Karadeniz Technical University Faculty of Medicine, Trabzon, Turkey
| | - Zeynep Aydoğan
- Department of Radiology, Karadeniz Technical University Faculty of Medicine, Trabzon, Turkey
| | - Sinan Erdemi
- Department of Radiology, Tokat State Hospital, Tokat, Turkey
| | - Aykut Teymur
- Department of Radiology, Faculty of Medicine, Karadeniz Technical University, Trabzon, Turkey
| | - Onur Bektaş
- Department of Radiology, Karadeniz Technical University Faculty of Medicine, Trabzon, Turkey
| | - Sevdegül Mungan
- Department of Pathology, Faculty of Medicine, Karadeniz Technical University, Trabzon, Turkey
| | - İlke Onur Kazaz
- Department of Urology, Faculty of Medicine, Karadeniz Technical University, Trabzon, Turkey
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Chartier S, Arif-Tiwari H. MR Virtual Biopsy of Solid Renal Masses: An Algorithmic Approach. Cancers (Basel) 2023; 15:2799. [PMID: 37345136 DOI: 10.3390/cancers15102799] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 05/12/2023] [Accepted: 05/12/2023] [Indexed: 06/23/2023] Open
Abstract
Between 1983 and 2002, the incidence of solid renal tumors increased from 7.1 to 10.8 cases per 100,000. This is in large part due to the increase in the volume of ultrasound and cross-sectional imaging, although a majority of solid renal tumors are still found incidentally. Ultrasound and computed tomography (CT) have been the mainstay of renal mass screening and diagnosis but recent advances in magnetic resonance (MR) technology have made this the optimal choice when diagnosing and staging renal tumors. Our purpose in writing this review is to survey the modern MR imaging approach to benign and malignant solid renal tumors, consolidate the various imaging findings into an easy-to-read reference, and provide an imaging-based, algorithmic approach to renal mass characterization for clinicians. MR is at the forefront of renal mass characterization, surpassing ultrasound and CT in its ability to describe multiple tissue parameters and predict tumor biology. Cutting-edge MR protocols and the integration of diagnostic algorithms can improve patient outcomes, allowing the imager to narrow the differential and better guide oncologic and surgical management.
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Affiliation(s)
- Stephane Chartier
- Department of Medical Imaging, College of Medicine, The University of Arizona, Tucson, AZ 85724, USA
| | - Hina Arif-Tiwari
- Department of Medical Imaging, College of Medicine, The University of Arizona, Tucson, AZ 85724, USA
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Comparative diagnostic performance of contrast-enhanced ultrasound and dynamic contrast-enhanced magnetic resonance imaging for differentiating clear cell and non-clear cell renal cell carcinoma. Eur Radiol 2023; 33:3766-3774. [PMID: 36725722 DOI: 10.1007/s00330-023-09391-9] [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: 06/14/2022] [Revised: 12/09/2022] [Accepted: 12/23/2022] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To compare the diagnostic efficiency of contrast-enhanced ultrasound (CEUS) with that of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for the differential diagnosis of clear and non-clear cell renal cell carcinoma, as confirmed by subsequent pathology. METHODS A total of 181 patients with 184 renal lesions diagnosed by both CEUS and DCE-MRI were enrolled in the study, including 136 clear cell renal cell carcinoma (ccRCC) and 48 non-clear cell renal cell carcinoma (non-ccRCC) tumors. All lesions were confirmed by histopathologic diagnosis after surgical resection. Interobserver agreement was estimated using a weighted kappa statistic. Diagnostic efficiency in evaluating ccRCC and non-ccRCC was compared between CEUS and DCE-MRI. RESULTS The weighted kappa value for interobserver agreement was 0.746 to 0.884 for CEUS diagnosis and 0.764 to 0.895 for DCE-MRI diagnosis. Good diagnostic performance in differential diagnosis of ccRCC and non-ccRCC was displayed by both CEUS and DCE-MRI: sensitivity was 89.7% and 91.9%, respectively; specificity was 77.1% and 68.8%, respectively; and area under the receiver operating curve was 0.834 and 0.803, respectively. No statistically significant differences were present between the two methods (p = 0.54). CONCLUSIONS Both CEUS and DCE-MRI imaging are effective for the differential diagnosis of ccRCC and non-ccRCC. Thus, CEUS could be an alternative to DCE-MRI as a first test for patients at risk of renal cancer, particularly where DCE-MRI cannot be carried out. KEY POINTS • CEUS and DCE-MRI features can help differentiate ccRCC and non-ccRCC. • The differential diagnosis of ccRCC and non-ccRCC by CEUS is comparable to that of DCE-MRI. • Interobserver agreement is generally high using CEUS and DCE-MRI.
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Pietersen PI, Lynggård Bo Madsen J, Asmussen J, Lund L, Nielsen TK, Pedersen M, Engvad B, Graumann O. Multiparametric magnetic resonance imaging for characterizing renal tumors: A validation study of the algorithm presented by Cornelis et al. J Clin Imaging Sci 2023; 13:7. [PMID: 36908585 PMCID: PMC9992978 DOI: 10.25259/jcis_124_2022] [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: 10/15/2022] [Accepted: 01/17/2023] [Indexed: 02/05/2023] Open
Abstract
Objectives In the last decade, the incidence of renal cell carcinoma (RCC) has been rising, with the greatest increase observed for solid tumors. Magnetic resonance imaging (MRI) protocols and algorithms have recently been available for classifying RCC subtypes and benign subtypes. The objective of this study was to prospectively validate the MRI algorithm presented by Cornelis et al. for RCC classification. Material and Methods Over a 7-month period, 38 patients with 44 renal tumors were prospectively included in the study and received an MRI examination in addition to the conventional investigation program. The MRI sequences were: T2-weighted, dual chemical shift MRI, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced T1-weighted in wash-in and wash-out phases. The images were evaluated according to the algorithm by two experienced, blinded radiologists, and the histopathological diagnosis served as the gold standard. Results Of 44 tumors in 38 patients, only 8 tumors (18.2%) received the same MRI diagnosis according to the algorithm as the histopathological diagnosis. MRI diagnosed 16 angiomyolipoma, 14 clear cell RCC (ccRCC), 12 chromophobe RCC (chRCC), and two papillary RCC (pRCC), while histopathological examination diagnosed 24 ccRCC, four pRCC, one chRCC, and one mixed tumor of both pRCC and chRCC. Malignant tumors were statistically significantly larger than the benign (3.16 ± 1.34 cm vs. 2.00 ± 1.04 cm, P = 0.006). Conclusion This prospective study could not reproduce Cornelis et al.'s results and does not support differentiating renal masses using multiparametric MRI without percutaneous biopsy in the future. The MRI algorithm showed few promising results to categorize renal tumors, indicating histopathology for clinical decisions and follow-up regimes of renal masses are still required.
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Affiliation(s)
| | - Janni Lynggård Bo Madsen
- Research and Innovation Unit, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Jon Asmussen
- Department of Radiology, Odense University Hospital, Odense, Denmark
| | - Lars Lund
- Department of Urology, Odense University Hospital, Odense, Denmark
| | | | - Michael Pedersen
- Department of Clinical Medicine - Comparative Medicine Lab, Aarhus University Hospital, Aarhus, Denmark
| | - Birte Engvad
- Department of Pathology, Odense University Hospital, Odense, Denmark
| | - Ole Graumann
- Department of Radiology, Odense University Hospital, Odense, Denmark
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Richard PO, Violette PD, Bhindi B, Breau RH, Kassouf W, Lavallée LT, Jewett M, Kachura JR, Kapoor A, Noel-Lamy M, Ordon M, Pautler SE, Pouliot F, So AI, Rendon RA, Tanguay S, Collins C, Kandi M, Shayegan B, Weller A, Finelli A, Kokorovic A, Nayak J. Canadian Urological Association guideline: Management of small renal masses - Full-text. Can Urol Assoc J 2022; 16:E61-E75. [PMID: 35133268 PMCID: PMC8932428 DOI: 10.5489/cuaj.7763] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2023]
Affiliation(s)
- Patrick O. Richard
- Department of Surgery, Division of Urology, Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, QC, Canada
| | - Philippe D. Violette
- Departments of Health Research Methods Evidence and Impact (HEI) and Surgery, McMaster University, Hamilton, ON, Canada
| | - Bimal Bhindi
- Southern Alberta Institute of Urology, University of Calgary, Calgary, AB, Canada
| | - Rodney H. Breau
- Department of Surgery, Division of Urology, University of Ottawa, Ottawa, ON, Canada
| | - Wassim Kassouf
- Department of Surgery, Division of Urology, McGill University Health Centre, Montreal, QC, Canada
| | - Luke T. Lavallée
- Department of Surgery, Division of Urology, University of Ottawa, Ottawa, ON, Canada
| | - Michael Jewett
- Department of Surgical Oncology, Division of Urology, Princess Margaret Hospital, Toronto, ON, Canada
| | - John R. Kachura
- Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, ON, Canada
| | - Anil Kapoor
- McMaster Institute of Urology, St. Joseph Healthcare, Hamilton, ON, Canada
| | - Maxime Noel-Lamy
- Department of Medical Imaging, Division of Interventional Radiology, Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, QC, Canada
| | - Michael Ordon
- Department of Surgery, Division of Urology, St. Michael’s Hospital, Toronto, ON, Canada
| | - Stephen E. Pautler
- Department of Surgery, Division of Urology, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Frédéric Pouliot
- Department of Surgery, Division of Urology, Centre Hospitalier Universitaire de Québec, Quebec, QC, Canada
| | - Alan I. So
- Division of Urology, British Columbia Cancer Care, Vancouver, BC, Canada
| | - Ricardo A. Rendon
- Department of Surgery, Division of Urology, Capital Health - QEII, Halifax, NS, Canada
| | - Simon Tanguay
- Department of Surgery, Division of Urology, McGill University Health Centre, Montreal, QC, Canada
| | | | - Maryam Kandi
- Departments of Health Research Methods Evidence and Impact (HEI) and Surgery, McMaster University, Hamilton, ON, Canada
| | - Bobby Shayegan
- McMaster Institute of Urology, St. Joseph Healthcare, Hamilton, ON, Canada
| | | | - Antonio Finelli
- Department of Surgical Oncology, Division of Urology, Princess Margaret Hospital, Toronto, ON, Canada
| | - Andrea Kokorovic
- Centre Hospitalier de l’Université de Montréal, Montreal, QC, Canada
| | - Jay Nayak
- Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
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11
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YANG Z, LI M, GUO A, LIANG Y, FANG P. Imaging features and clinic value of mri and ct in diagnosis of clear cell renal cell carcinoma. FOOD SCIENCE AND TECHNOLOGY 2022. [DOI: 10.1590/fst.40520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Affiliation(s)
| | - Ming LI
- Henan Province Hospital of TCM, China
| | - Aiju GUO
- Henan Province Hospital of TCM, China
| | | | - Peng FANG
- Henan Province Hospital of TCM, China
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12
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Zaytoun OM, Darweesh RM, Gaber SA, Ibrahim RM. Role of non-contrast magnetic resonance imaging in pre-surgical evaluation of renal masses in renal impairment patients. AFRICAN JOURNAL OF UROLOGY 2021. [DOI: 10.1186/s12301-021-00165-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
The aim of this work is to study the role of non-contrast MRI in pre-surgical evaluation of renal masses in renal impairment patients as confirmed by both intraoperative and histopathological findings. Intraoperative and histopathological findings were correlated with radiological data.
Methods
This prospective study included 20 patients comprising 25 renal masses. The data were collected in a period from April 2018 to September 2019. All patients underwent partial or radical nephrectomy by the same surgeon.
Results
Based on MRI findings, 9 masses (36%) and 8 masses (32%) were found to be associated with collecting system invasion and perinephric fat invasion, respectively. Histopathological assessment confirmed only 6 cases (24%) with collecting system invasion and 7 cases (28%) demonstrated perinephric fat. Seven masses (28%) had intralesional hemorrhage detected by MRI and confirmed by pathological findings. The MRI detected 6 cases (24%) with lymph nodes invasion, while the histopathological assessment confirmed lymphatic invasion in 7 cases (28%). Only 2 cases (8%) had vascular invasion detected by preoperative MRI and confirmed by histopathology and surgery. The final histopathological examination confirmed 20 malignant neoplasms (80%: RCC = 18, leiomyosarcoma = 2), 3 benign neoplasms (12%: angiomyolipoma = 1, oncocytoma = 2) and 2 non-neoplastic benign masses (8%: renal abscess = 1, xanthogranulomatous pyelonephritis = 1).
Conclusion
Non-contrast MRI is a crucial imaging tool in renal impairment patients who cannot be examined with contrast-enhanced CT or MRI. It assesses the extent of the renal sinus fat and the perinephric fat invasion.
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13
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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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14
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Chen XY, Zhang Y, Chen YX, Huang ZQ, Xia XY, Yan YX, Xu MP, Chen W, Wang XL, Chen QL. MRI-Based Grading of Clear Cell Renal Cell Carcinoma Using a Machine Learning Classifier. Front Oncol 2021; 11:708655. [PMID: 34660276 PMCID: PMC8517330 DOI: 10.3389/fonc.2021.708655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Accepted: 09/15/2021] [Indexed: 11/14/2022] Open
Abstract
Objective To develop a machine learning (ML)-based classifier for discriminating between low-grade (ISUP I-II) and high-grade (ISUP III-IV) clear cell renal cell carcinomas (ccRCCs) using MRI textures. Materials and Methods We retrospectively evaluated a total of 99 patients (with 61 low-grade and 38 high-grade ccRCCs), who were randomly divided into a training set (n = 70) and a validation set (n = 29). Regions of interest (ROIs) of all tumors were manually drawn three times by a radiologist at the maximum lesion level of the cross-sectional CMP sequence images. The quantitative texture analysis software, MaZda, was used to extract texture features, including histograms, co-occurrence matrixes, run-length matrixes, gradient models, and autoregressive models. Reproducibility of the texture features was assessed with the intra-class correlation coefficient (ICC). Features were chosen based on their importance coefficients in a random forest model, while the multi-layer perceptron algorithm was used to build a classifier on the training set, which was later evaluated with the validation set. Results The ICCs of 257 texture features were equal to or higher than 0.80 (0.828–0.998. Six features, namely Kurtosis, 135dr_RLNonUni, Horzl_GLevNonU, 135dr_GLevNonU, S(4,4)Entropy, and S(0,5)SumEntrp, were chosen to develop the multi-layer perceptron classifier. A three-layer perceptron model, which has 229 nodes in the hidden layer, was trained on the training set. The accuracy of the model was 95.7% with the training set and 86.2% with the validation set. The areas under the receiver operating curves were 0.997 and 0.758 for the training and validation sets, respectively. Conclusions A machine learning-based grading model was developed that can aid in the clinical diagnosis of clear cell renal cell carcinoma using MRI images.
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Affiliation(s)
- Xin-Yuan Chen
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
| | - Yu Zhang
- Department of Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.,Department of Radiology, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, China
| | - Yu-Xing Chen
- Department of Bioinformatics, School of Basic Medical Sciences, School of Medical Technology and Engineering, Key Laboratory of Medical Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China
| | - Zi-Qiang Huang
- Department of Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
| | - Xiao-Yue Xia
- Department of Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
| | - Yi-Xin Yan
- Department of Bioinformatics, School of Basic Medical Sciences, School of Medical Technology and Engineering, Key Laboratory of Medical Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China
| | - Mo-Ping Xu
- Department of Bioinformatics, School of Basic Medical Sciences, School of Medical Technology and Engineering, Key Laboratory of Medical Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China
| | - Wen Chen
- Department of Bioinformatics, School of Basic Medical Sciences, School of Medical Technology and Engineering, Key Laboratory of Medical Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China
| | - Xian-Long Wang
- Department of Bioinformatics, School of Basic Medical Sciences, School of Medical Technology and Engineering, Key Laboratory of Medical Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China
| | - Qun-Lin Chen
- Department of Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
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15
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Suo X, Chen J, Zhao Y, Tang Q, Yang X, Yuan Y, Nie L, Chen N, Zeng H, Yao J. Clinicopathological and radiological significance of the collateral vessels of renal cell carcinoma on preoperative computed tomography. Sci Rep 2021; 11:5187. [PMID: 33664382 PMCID: PMC7933355 DOI: 10.1038/s41598-021-84631-w] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Accepted: 02/05/2021] [Indexed: 02/05/2023] Open
Abstract
This study aimed to investigate the clinicopathological and radiological significance of the collateral vessel of renal cell carcinoma (RCC) on preoperative computed tomography (CT). Preoperative contrast-enhanced CT of 236 consecutive patients with pathological documented RCC were retrospectively reviewed during the period of 2014. The associations of the presence of collateral vessels with perioperative clinicopathological and radiological features, as well as long term survival outcomes were analyzed. Totally, collateral vessels were detected by contrast-enhanced CT in 110 of 236 patients. The presence of collateral vessels was significantly associated with higher pathologic T stage, higher Fuhrman grade, higher overall RENAL scores, greater tumor size and enhancement, and more tumor necrosis (all P < 0.05). In patients with clear cell RCC, those harboring collateral vessels had significantly higher SSIGN scores (P < 0.001) and shorter overall survival (P = 0.01) than those without collateral vessel. The incidence of intraoperative blood loss, blood transfusion, radical nephrectomy (RN) and open surgery were also significantly higher in patients with collateral vessels (all P < 0.05). In multivariate analysis, the presence of collateral vessels was significantly associated with RN (P = 0.021) and open surgery (P = 0.012). The presence of collateral vessels was significantly associated with aggressive clinicopathological parameters and worse prognosis. It is worth paying attention to its association with the choice of RN and open surgery in clinical practice.
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Affiliation(s)
- Xueling Suo
- Department of Radiology, West China Hospital of Sichuan University, No. 37 Guo Xue Xiang, Chengdu, 610041, Sichuan, China
| | - Junru Chen
- Department of Urology, Institute of Urology, West China Hospital of Sichuan University, No. 37 Guo Xue Xiang, Chengdu, 610041, Sichuan, China
| | - Yijun Zhao
- Department of Radiology, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Qidun Tang
- Department of Urology, Chengdu Second People's Hospital, Chengdu, 610017, Sichuan, China
| | - Xibiao Yang
- Department of Radiology, West China Hospital of Sichuan University, No. 37 Guo Xue Xiang, Chengdu, 610041, Sichuan, China
| | - Yuan Yuan
- Department of Radiology, West China Hospital of Sichuan University, No. 37 Guo Xue Xiang, Chengdu, 610041, Sichuan, China
| | - Ling Nie
- Department of Pathology, West China Hospital of Sichuan University, Chengdu, 610041, Sichuan, China
| | - Ni Chen
- Department of Pathology, West China Hospital of Sichuan University, Chengdu, 610041, Sichuan, China
| | - Hao Zeng
- Department of Urology, Institute of Urology, West China Hospital of Sichuan University, No. 37 Guo Xue Xiang, Chengdu, 610041, Sichuan, China.
| | - Jin Yao
- Department of Radiology, West China Hospital of Sichuan University, No. 37 Guo Xue Xiang, Chengdu, 610041, Sichuan, China.
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16
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Xu HS, Balcacer P, Zhang Z, Zhang L, Yee EU, Sun MR, Tsai LL. Characterizing T2 iso- and hypo-intense renal masses on MRI: Can templated algorithms improve accuracy? Clin Imaging 2020; 72:47-54. [PMID: 33217669 DOI: 10.1016/j.clinimag.2020.10.051] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2020] [Revised: 10/03/2020] [Accepted: 10/29/2020] [Indexed: 10/23/2022]
Abstract
PURPOSE To assess if a templated algorithm can improve the diagnostic performance of MRI for characterization of T2 isointense and hypointense renal masses. METHODS In this retrospective study, 60 renal masses with histopathologic diagnoses that were also confirmed as T2 iso- or hypointense on MRI were identified (mean ± standard deviation, range: 3.9 ± 2.5, 1.0-13.7 cm). Two semi-quantitative diagnostic algorithms were created based on MRI features of renal masses reported in the literature. Three body-MRI trained radiologists provided clinical diagnoses based on their experience and separately provided semiquantitative data for each components of the two algorithms. The algorithms were applied separately by a radiology trainee without additional interpretive input. Logistic regression was used to compare the accuracy of the three methods in distinguishing malignant versus benign lesions and in diagnosing the exact histopathology. Inter-reader agreement for each method was calculated using Fleiss' kappa statistics. RESULTS The accuracy of the two algorithms and clinical experience were similar (70%, 69%, and 64%, respectively, p = 0.22-0.32), with fair to moderate inter-reader agreement (Fleiss's kappa: r = 0.375, r = 0.308, r = 0.375, respectively, all p < 0.0001). The accuracy of the two algorithms and clinical experience in diagnosing specific histopathology were also no different from each other (34%, 29%, and 32%, respectively, p = 0.49-0.74), with fair to moderate inter-reader agreement (Fleiss's kappa: r = 0.20, r = 0.28, r = 0.375, respectively, all p < 0.0001). CONCLUSION Semi-quantitative templated algorithms based on MRI features of renal masses did not improve the ability to diagnose T2 iso- and hypointense renal masses when compared to unassisted interpretation by body MR trained subspecialists.
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Affiliation(s)
- Helen S Xu
- Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Boston, MA 02215, United States of America; New York Presbyterian Weill Cornell Medical Center, 525 East 68th Street, New York, NY 10065, United States of America.
| | - Patricia Balcacer
- Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Boston, MA 02215, United States of America
| | - Zheng Zhang
- Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Boston, MA 02215, United States of America
| | - Liang Zhang
- Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Boston, MA 02215, United States of America
| | - Eric U Yee
- University of Arkansas for Medical Sciences, 4301 W. Markham St., #517, Little Rock, AR 72205, United States of America
| | - Maryellen R Sun
- Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Boston, MA 02215, United States of America
| | - Leo L Tsai
- Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Boston, MA 02215, United States of America
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17
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Schwarze V, Rübenthaler J, Marschner C, Fabritius MP, Rueckel J, Fink N, Puhr-Westerheide D, Gresser E, Froelich MF, Schnitzer ML, Große Hokamp N, Afat S, Staehler M, Geyer T, Clevert DA. Advanced Fusion Imaging and Contrast-Enhanced Imaging (CT/MRI-CEUS) in Oncology. Cancers (Basel) 2020; 12:E2821. [PMID: 33007933 PMCID: PMC7600560 DOI: 10.3390/cancers12102821] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2020] [Revised: 09/24/2020] [Accepted: 09/28/2020] [Indexed: 02/07/2023] Open
Abstract
Fusion imaging depicts an innovative technique that facilitates combining assets and reducing restrictions of advanced ultrasound and cross-sectional imaging. The purpose of the present retrospective study was to evaluate the role of fusion imaging for assessing hepatic and renal lesions. Between 02/2011-08/2020, 92 patients in total were included in the study, of which 32 patients had hepatic lesions, 60 patients had renal lesions. Fusion imaging was technically successful in all patients. No adverse side effects upon intravenous (i.v.) application of SonoVue® (Bracco, Milan, Italy) were registered. Fusion imaging could clarify all 11 (100%) initially as indeterminate described hepatic lesions by computed tomography/magnetic resonance imaging (CT/MRI). Moreover, 5/14 (36%) initially suspicious hepatic lesions could be validated by fusion imaging, whereas in 8/14 (57%), malignant morphology was disproved. Moreover, fusion imaging allowed for the clarification of 29/30 (97%) renal lesions initially characterized as suspicious by CT/MRI, of which 19/30 (63%) underwent renal surgery, histopathology revealed malignancy in 16/19 (84%), and benignity in 3/19 (16%). Indeterminate findings could be elucidated by fusion imaging in 20/20 (100%) renal lesions. Its accessibility and repeatability, even during pregnancy and in childhood, its cost-effectiveness, and its excellent safety profile, make fusion imaging a promising instrument for the thorough evaluation of hepatic and renal lesions in the future.
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Affiliation(s)
- Vincent Schwarze
- Department of Radiology, University Hospital LMU, Marchioninistrasse 15, 81377 Munich, Germany; (J.R.); (C.M.); (M.P.F.); (J.R.); (N.F.); (D.P.-W.); (E.G.); (M.L.S.); (T.G.); (D.-A.C.)
| | - Johannes Rübenthaler
- Department of Radiology, University Hospital LMU, Marchioninistrasse 15, 81377 Munich, Germany; (J.R.); (C.M.); (M.P.F.); (J.R.); (N.F.); (D.P.-W.); (E.G.); (M.L.S.); (T.G.); (D.-A.C.)
| | - Constantin Marschner
- Department of Radiology, University Hospital LMU, Marchioninistrasse 15, 81377 Munich, Germany; (J.R.); (C.M.); (M.P.F.); (J.R.); (N.F.); (D.P.-W.); (E.G.); (M.L.S.); (T.G.); (D.-A.C.)
| | - Matthias Philipp Fabritius
- Department of Radiology, University Hospital LMU, Marchioninistrasse 15, 81377 Munich, Germany; (J.R.); (C.M.); (M.P.F.); (J.R.); (N.F.); (D.P.-W.); (E.G.); (M.L.S.); (T.G.); (D.-A.C.)
| | - Johannes Rueckel
- Department of Radiology, University Hospital LMU, Marchioninistrasse 15, 81377 Munich, Germany; (J.R.); (C.M.); (M.P.F.); (J.R.); (N.F.); (D.P.-W.); (E.G.); (M.L.S.); (T.G.); (D.-A.C.)
| | - Nicola Fink
- Department of Radiology, University Hospital LMU, Marchioninistrasse 15, 81377 Munich, Germany; (J.R.); (C.M.); (M.P.F.); (J.R.); (N.F.); (D.P.-W.); (E.G.); (M.L.S.); (T.G.); (D.-A.C.)
| | - Daniel Puhr-Westerheide
- Department of Radiology, University Hospital LMU, Marchioninistrasse 15, 81377 Munich, Germany; (J.R.); (C.M.); (M.P.F.); (J.R.); (N.F.); (D.P.-W.); (E.G.); (M.L.S.); (T.G.); (D.-A.C.)
| | - Eva Gresser
- Department of Radiology, University Hospital LMU, Marchioninistrasse 15, 81377 Munich, Germany; (J.R.); (C.M.); (M.P.F.); (J.R.); (N.F.); (D.P.-W.); (E.G.); (M.L.S.); (T.G.); (D.-A.C.)
| | - Matthias Frank Froelich
- Institute of Clinical Radiology and Nuclear Medicine, University Medical Center Mannheim, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany;
| | - Moritz Ludwig Schnitzer
- Department of Radiology, University Hospital LMU, Marchioninistrasse 15, 81377 Munich, Germany; (J.R.); (C.M.); (M.P.F.); (J.R.); (N.F.); (D.P.-W.); (E.G.); (M.L.S.); (T.G.); (D.-A.C.)
| | - Nils Große Hokamp
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University Cologne, Kerpener Str. 62, 50937 Cologne, Germany;
| | - Saif Afat
- Department for Diagnostic and Interventional Radiology, Eberhard Karls University Tuebingen, University Hospital Tuebingen, Hoppe-Seyler-Str. 3, 72076 Tuebingen, Germany;
| | - Michael Staehler
- Department of Urology, University Hospital LMU, Marchioninistrasse 15, 81377 Munich, Germany;
| | - Thomas Geyer
- Department of Radiology, University Hospital LMU, Marchioninistrasse 15, 81377 Munich, Germany; (J.R.); (C.M.); (M.P.F.); (J.R.); (N.F.); (D.P.-W.); (E.G.); (M.L.S.); (T.G.); (D.-A.C.)
| | - Dirk-André Clevert
- Department of Radiology, University Hospital LMU, Marchioninistrasse 15, 81377 Munich, Germany; (J.R.); (C.M.); (M.P.F.); (J.R.); (N.F.); (D.P.-W.); (E.G.); (M.L.S.); (T.G.); (D.-A.C.)
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18
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Chu JS, Wang ZJ. Protocol Optimization for Renal Mass Detection and Characterization. Radiol Clin North Am 2020; 58:851-873. [PMID: 32792119 DOI: 10.1016/j.rcl.2020.05.003] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
Renal masses increasingly are found incidentally, largely due to the frequent use of medical imaging. Computed tomography (CT) and MR imaging are mainstays for renal mass characterization, presurgical planning of renal tumors, and surveillance after surgery or systemic therapy for advanced renal cell carcinomas. CT protocols should be tailored to different clinical indications, balancing diagnostic accuracy and radiation exposure. MR imaging protocols should take advantage of the improved soft tissue contrast for renal tumor diagnosis and staging. Optimized imaging protocols enable analysis of imaging features that help narrow the differential diagnoses and guide management in patients with renal masses.
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Affiliation(s)
- Jason S Chu
- Department of Radiology and Biomedical Imaging, University of California San Francisco, 505 Parnassus Avenue, Box 0628, San Francisco, CA 94143, USA
| | - Zhen J Wang
- Department of Radiology and Biomedical Imaging, University of California San Francisco, 505 Parnassus Avenue, Box 0628, San Francisco, CA 94143, USA.
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19
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Contrast-Enhanced Ultrasound (CEUS) for Follow-Up of Bosniak 2F Complex Renal Cystic Lesions-A 12-Year Retrospective Study in a Specialized European Center. Cancers (Basel) 2020; 12:cancers12082170. [PMID: 32759819 PMCID: PMC7465614 DOI: 10.3390/cancers12082170] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Revised: 07/28/2020] [Accepted: 08/03/2020] [Indexed: 02/07/2023] Open
Abstract
Bosniak 2F renal cystic lesions feature morphologic characteristics between Bosniak I and III categories, the majority of which remain benign. However, a minor part of Bosniak 2F lesions may progress to malignancy. The purpose of this study was to assess Bosniak 2F cystic lesions during follow-up examinations by CEUS. One-hundred-and-twelve out of 364 patients with Bosniak 2F lesions underwent follow-up CEUS examinations between February 2008 and February 2020. Twelve out of 364 patients underwent renal surgery without follow-up CEUS. The progression rate of Bosniak 2F renal lesions detected by CEUS accounted for 7.1% (8/112 patients) after a mean of 12.9 months. The first follow-up CEUS revealed 75% of progressions (6/8), the remaining 25% (2/8) of progressions were detected during second follow-up CEUS. Underlying clear-cell renal cell carcinoma was histopathologically validated in 5/8 progressive complex cystic renal lesions. Stable sonomorphologic features were observed in 92.1% (104/112 patients). CEUS depicts a promising diagnostic imaging modality in the diagnostic work-up and follow-up of complex renal cystic lesions at higher spatial and temporal resolutions than CT or MRI. Its excellent safety profile, its easy and repeatable accessibility, and low financial costs render CEUS an attractive and powerful alternative imaging tool for monitoring complex renal cystic lesions.
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20
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Li Q, Liu YJ, Dong D, Bai X, Huang QB, Guo AT, Ye HY, Tian J, Wang HY. Multiparametric MRI Radiomic Model for Preoperative Predicting WHO/ISUP Nuclear Grade of Clear Cell Renal Cell Carcinoma. J Magn Reson Imaging 2020; 52:1557-1566. [PMID: 32462799 DOI: 10.1002/jmri.27182] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Revised: 04/14/2020] [Accepted: 04/17/2020] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Nuclear grade is of importance for treatment selection and prognosis in patients with clear cell renal cell carcinoma (ccRCC). PURPOSE To develop and validate an MRI-based radiomic model for preoperative predicting WHO/ISUP nuclear grade in ccRCC. STUDY TYPE Retrospective. POPULATION In all, 379 patients with histologically confirmed ccRCC. Training cohort (n = 252) and validation cohort (n = 127) were randomly assigned. FIELD STRENGTH/SEQUENCE Pretreatment 3.0T renal MRI. Imaging sequences were fat-suppressed T2 WI, contrast-enhanced T1 WI, and diffusion weighted imaging. ASSESSMENT Three prediction models were developed using selected radiomic features, radiomic and clinicoradiologic characteristics, and a model containing only clinicoradiologic characteristics. Receiver operating characteristic (ROC) curves and area under the curve (AUC) were used to assess the predictive performance of these models in predicting high-grade ccRCC. STATISTICAL TESTS The least absolute shrinkage and selection operator (LASSO) and minimum redundancy maximum relevance (mRMR) method were used for the selection of radiomic features and clinicoradiologic characteristics, respectively. Multivariable logistic regression analysis was used to develop the radiomic signature of radiomic features and clinicoradiologic model of clinicoradiologic characteristics. RESULTS The radiomic signature showed good performance in discriminating high-grade (grades 3 and 4) from low-grade (grades 1 and 2) ccRCC, with sensitivity, specificity, and AUC of 77.3%, 80.0%, and 0.842, respectively, in the validation cohort. The radiomic model, combining radiomic signature and clinicoradiologic characteristics, displayed good predictive ability for high-grade with sensitivity, specificity, and accuracy of 63.6%, 93.3%, and 88.2%, respectively, in the validation cohort. The radiomic model showed a significantly better performance than the clinicoradiologic model (P < 0.05). DATA CONCLUSION Multiparametric MRI-based radiomic model can predict WHO/ISUP grade in patients with ccRCC with satisfying performance, and thus could help the physician to improve treatment decisions. LEVEL OF EVIDENCE 3 TECHNICAL EFFICACY STAGE: 2.
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Affiliation(s)
- Qiong Li
- Department of Radiology, Tianjin Nankai Hospital (Tianjin Hospital of Integrated Traditional Chinese and Western Medicine), Tianjin, China.,Department of Radiology, First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Yu-Jia Liu
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China.,CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Di Dong
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China.,CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Xu Bai
- Department of Radiology, First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Qing-Bo Huang
- Department of Urology, First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Ai-Tao Guo
- Department of Pathology, First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Hui-Yi Ye
- Department of Radiology, First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Jie Tian
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine, Beihang University, Beijing, China
| | - Hai-Yi Wang
- Department of Radiology, First Medical Center, Chinese PLA General Hospital, Beijing, China
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Quantitative Analysis of Multiphase Contrast-Enhanced CT Images: A Pilot Study of Preoperative Prediction of Fat-Poor Angiomyolipoma and Renal Cell Carcinoma. AJR Am J Roentgenol 2019; 214:370-382. [PMID: 31799870 DOI: 10.2214/ajr.19.21625] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
OBJECTIVE. The objective of our study was to preoperatively predict fat-poor angiomyolipoma (fp-AML) and renal cell carcinoma (RCC) by conducting quantitative analysis of contrast-enhanced CT images. MATERIALS AND METHODS. One hundred fifteen patients with a pathologic diagnosis of fp-AML or RCC from a single institution were randomly allocated into a train set (tumor size: mean ± SD, 4.50 ± 2.62 cm) and test set (tumor size: 4.32 ± 2.73 cm) after data augmentation. High-dimensional histogram-based features, texture-based features, and Laws features were first extracted from CT images and were then combined as different combinations sets to construct a logistic prediction model based on the least absolute shrinkage and selection operator procedure for the prediction of fp-AML and RCC. Prediction performances were assessed by classification accuracy, area under the ROC curve (AUC), positive predictive value, negative predictive value, true-positive rate, and false-positive rate (FPR). In addition, we also investigated the effects of different gray-scales of quantitative features on prediction performances. RESULTS. The following combination sets of features achieved satisfying performances in the test set: histogram-based features (mean AUC = 0.8492, mean classification accuracy = 91.01%); histogram-based features and texture-based features (mean AUC = 0.9244, mean classification accuracy = 91.81%); histogram-based features and Laws features (mean AUC = 0.8546, mean classification accuracy = 88.76%); and histogram-based features, texture-based features, and Laws features (mean AUC = 0.8925, mean classification accuracy = 90.36%). The different quantitative gray-scales did not have an obvious effect on prediction performances. CONCLUSION. The integration of histogram-based features with texture-based features and Laws features provided a potential biomarker for the preoperative diagnosis of fp-AML and RCC. The accurate diagnosis of benign or malignant renal masses would help to make the clinical decision for radical surgery or close follow-up.
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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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Can MRI be used to diagnose histologic grade in T1a (< 4 cm) clear cell renal cell carcinomas? Abdom Radiol (NY) 2019; 44:2841-2851. [PMID: 31041495 DOI: 10.1007/s00261-019-02018-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
OBJECTIVE To assess whether MRI can differentiate low-grade from high-grade T1a cc-RCC. MATERIALS AND METHODS With IRB approval, 49 consecutive solid < 4 cm cc-RCC (low grade [Grade 1 or 2] N = 38, high grade [Grade 3] N = 11) with pre-operative MRI before nephrectomy were identified between 2013 and 2018. Tumor size, apparent diffusion coefficient (ADC) histogram analysis, enhancement wash-in and wash-out rates, and chemical shift signal intensity index (SI index) were assessed by a blinded radiologist. Subjectively, two blinded Radiologists also assessed for (1) microscopic fat, (2) homogeneity (5-point Likert scale), and (3) ADC signal (relative to renal cortex); discrepancies were resolved by consensus. Outcomes were studied using Chi square, multivariate analysis, logistic regression modeling, and ROC. Inter-observer agreement was assessed using Cohen's kappa. RESULTS Tumor size was 24 ± 7 (13-39) mm with no association to grade (p = 0.45). Among quantitative features studied, corticomedullary phase wash-in index (p = 0.015), SI index (p = 0.137), and tenth-centile ADC (p = 0.049) were higher in low-grade tumors. 36.8% (14/38) low-grade tumors versus zero high-grade tumors demonstrated microscopic fat (p = 0.015; Kappa = 0.67). Microscopic fat was specific for low-grade disease (100.0% [71.5-100.0]) with low sensitivity (36.8% [21.8-54.6]). Other subjective features did not differ between groups (p > 0.05). A logistic regression model combining microscopic fat + wash-in index + tenth-centile-ADC yielded area under ROC curve 0.98 (Confidence Intervals 0.94-1.0) with sensitivity/specificity 87.5%/100%. CONCLUSION The combination of microscopic fat, higher corticomedullary phase wash-in and higher tenth-centile ADC is highly accurate for diagnosis of low-grade disease among T1a clear cell RCC.
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Silverman SG, Pedrosa I, Ellis JH, Hindman NM, Schieda N, Smith AD, Remer EM, Shinagare AB, Curci NE, Raman SS, Wells SA, Kaffenberger SD, Wang ZJ, Chandarana H, Davenport MS. Bosniak Classification of Cystic Renal Masses, Version 2019: An Update Proposal and Needs Assessment. Radiology 2019; 292:475-488. [PMID: 31210616 DOI: 10.1148/radiol.2019182646] [Citation(s) in RCA: 245] [Impact Index Per Article: 49.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Cystic renal cell carcinoma (RCC) is almost certainly overdiagnosed and overtreated. Efforts to diagnose and treat RCC at a curable stage result in many benign neoplasms and indolent cancers being resected without clear benefit. This is especially true for cystic masses, which compared with solid masses are more likely to be benign and, when malignant, less aggressive. For more than 30 years, the Bosniak classification has been used to stratify the risk of malignancy in cystic renal masses. Although it is widely used and still effective, the classification does not formally incorporate masses identified at MRI or US or masses that are incompletely characterized but are highly likely to be benign, and it is affected by interreader variability and variable reported malignancy rates. The Bosniak classification system cannot fully differentiate aggressive from indolent cancers and results in many benign masses being resected. This proposed update to the Bosniak classification addresses some of these shortcomings. The primary modifications incorporate MRI, establish definitions for previously vague imaging terms, and enable a greater proportion of masses to enter lower-risk classes. Although the update will require validation, it aims to expand the number of cystic masses to which the Bosniak classification can be applied while improving its precision and accuracy for the likelihood of cancer in each class.
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Affiliation(s)
- Stuart G Silverman
- From the Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (S.G.S., A.B.S.); Disease-Focused Panel on Renal Cell Carcinoma, Society of Abdominal Radiology, Houston, Tex (S.G.S., I.P., N.M.H., N.S., A.D.S., E.M.R., A.B.S., N.E.C., S.S.R., S.A.W., S.D.K., Z.J.W., H.C., M.S.D.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); Departments of Radiology and Urology, Michigan Medicine, University of Michigan, 1500 E Medical Center Dr, B2-A209A, Ann Arbor, MI 48109 (J.H.E., N.E.C., S.D.K., M.S.D.); Department of Radiology, New York University Langone Medical Center, New York, NY (N.M.H., H.C.); Department of Radiology, University of Ottawa, Ottawa, Canada (N.S.); Department of Radiology, University of Alabama School of Medicine, Birmingham, Ala (A.D.S.); Imaging Institute and Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio (E.M.R.); Department of Radiology, David Geffen School of Medicine, UCLA Center for the Health Sciences, Los Angeles, Calif (S.S.R.); Department of Radiology, University of Wisconsin Hospital and Clinics, Madison, Wis (S.A.W.); and Department of Radiology, UCSF Medical Center, San Francisco, Calif (Z.J.W.)
| | - Ivan Pedrosa
- From the Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (S.G.S., A.B.S.); Disease-Focused Panel on Renal Cell Carcinoma, Society of Abdominal Radiology, Houston, Tex (S.G.S., I.P., N.M.H., N.S., A.D.S., E.M.R., A.B.S., N.E.C., S.S.R., S.A.W., S.D.K., Z.J.W., H.C., M.S.D.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); Departments of Radiology and Urology, Michigan Medicine, University of Michigan, 1500 E Medical Center Dr, B2-A209A, Ann Arbor, MI 48109 (J.H.E., N.E.C., S.D.K., M.S.D.); Department of Radiology, New York University Langone Medical Center, New York, NY (N.M.H., H.C.); Department of Radiology, University of Ottawa, Ottawa, Canada (N.S.); Department of Radiology, University of Alabama School of Medicine, Birmingham, Ala (A.D.S.); Imaging Institute and Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio (E.M.R.); Department of Radiology, David Geffen School of Medicine, UCLA Center for the Health Sciences, Los Angeles, Calif (S.S.R.); Department of Radiology, University of Wisconsin Hospital and Clinics, Madison, Wis (S.A.W.); and Department of Radiology, UCSF Medical Center, San Francisco, Calif (Z.J.W.)
| | - James H Ellis
- From the Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (S.G.S., A.B.S.); Disease-Focused Panel on Renal Cell Carcinoma, Society of Abdominal Radiology, Houston, Tex (S.G.S., I.P., N.M.H., N.S., A.D.S., E.M.R., A.B.S., N.E.C., S.S.R., S.A.W., S.D.K., Z.J.W., H.C., M.S.D.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); Departments of Radiology and Urology, Michigan Medicine, University of Michigan, 1500 E Medical Center Dr, B2-A209A, Ann Arbor, MI 48109 (J.H.E., N.E.C., S.D.K., M.S.D.); Department of Radiology, New York University Langone Medical Center, New York, NY (N.M.H., H.C.); Department of Radiology, University of Ottawa, Ottawa, Canada (N.S.); Department of Radiology, University of Alabama School of Medicine, Birmingham, Ala (A.D.S.); Imaging Institute and Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio (E.M.R.); Department of Radiology, David Geffen School of Medicine, UCLA Center for the Health Sciences, Los Angeles, Calif (S.S.R.); Department of Radiology, University of Wisconsin Hospital and Clinics, Madison, Wis (S.A.W.); and Department of Radiology, UCSF Medical Center, San Francisco, Calif (Z.J.W.)
| | - Nicole M Hindman
- From the Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (S.G.S., A.B.S.); Disease-Focused Panel on Renal Cell Carcinoma, Society of Abdominal Radiology, Houston, Tex (S.G.S., I.P., N.M.H., N.S., A.D.S., E.M.R., A.B.S., N.E.C., S.S.R., S.A.W., S.D.K., Z.J.W., H.C., M.S.D.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); Departments of Radiology and Urology, Michigan Medicine, University of Michigan, 1500 E Medical Center Dr, B2-A209A, Ann Arbor, MI 48109 (J.H.E., N.E.C., S.D.K., M.S.D.); Department of Radiology, New York University Langone Medical Center, New York, NY (N.M.H., H.C.); Department of Radiology, University of Ottawa, Ottawa, Canada (N.S.); Department of Radiology, University of Alabama School of Medicine, Birmingham, Ala (A.D.S.); Imaging Institute and Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio (E.M.R.); Department of Radiology, David Geffen School of Medicine, UCLA Center for the Health Sciences, Los Angeles, Calif (S.S.R.); Department of Radiology, University of Wisconsin Hospital and Clinics, Madison, Wis (S.A.W.); and Department of Radiology, UCSF Medical Center, San Francisco, Calif (Z.J.W.)
| | - Nicola Schieda
- From the Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (S.G.S., A.B.S.); Disease-Focused Panel on Renal Cell Carcinoma, Society of Abdominal Radiology, Houston, Tex (S.G.S., I.P., N.M.H., N.S., A.D.S., E.M.R., A.B.S., N.E.C., S.S.R., S.A.W., S.D.K., Z.J.W., H.C., M.S.D.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); Departments of Radiology and Urology, Michigan Medicine, University of Michigan, 1500 E Medical Center Dr, B2-A209A, Ann Arbor, MI 48109 (J.H.E., N.E.C., S.D.K., M.S.D.); Department of Radiology, New York University Langone Medical Center, New York, NY (N.M.H., H.C.); Department of Radiology, University of Ottawa, Ottawa, Canada (N.S.); Department of Radiology, University of Alabama School of Medicine, Birmingham, Ala (A.D.S.); Imaging Institute and Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio (E.M.R.); Department of Radiology, David Geffen School of Medicine, UCLA Center for the Health Sciences, Los Angeles, Calif (S.S.R.); Department of Radiology, University of Wisconsin Hospital and Clinics, Madison, Wis (S.A.W.); and Department of Radiology, UCSF Medical Center, San Francisco, Calif (Z.J.W.)
| | - Andrew D Smith
- From the Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (S.G.S., A.B.S.); Disease-Focused Panel on Renal Cell Carcinoma, Society of Abdominal Radiology, Houston, Tex (S.G.S., I.P., N.M.H., N.S., A.D.S., E.M.R., A.B.S., N.E.C., S.S.R., S.A.W., S.D.K., Z.J.W., H.C., M.S.D.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); Departments of Radiology and Urology, Michigan Medicine, University of Michigan, 1500 E Medical Center Dr, B2-A209A, Ann Arbor, MI 48109 (J.H.E., N.E.C., S.D.K., M.S.D.); Department of Radiology, New York University Langone Medical Center, New York, NY (N.M.H., H.C.); Department of Radiology, University of Ottawa, Ottawa, Canada (N.S.); Department of Radiology, University of Alabama School of Medicine, Birmingham, Ala (A.D.S.); Imaging Institute and Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio (E.M.R.); Department of Radiology, David Geffen School of Medicine, UCLA Center for the Health Sciences, Los Angeles, Calif (S.S.R.); Department of Radiology, University of Wisconsin Hospital and Clinics, Madison, Wis (S.A.W.); and Department of Radiology, UCSF Medical Center, San Francisco, Calif (Z.J.W.)
| | - Erick M Remer
- From the Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (S.G.S., A.B.S.); Disease-Focused Panel on Renal Cell Carcinoma, Society of Abdominal Radiology, Houston, Tex (S.G.S., I.P., N.M.H., N.S., A.D.S., E.M.R., A.B.S., N.E.C., S.S.R., S.A.W., S.D.K., Z.J.W., H.C., M.S.D.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); Departments of Radiology and Urology, Michigan Medicine, University of Michigan, 1500 E Medical Center Dr, B2-A209A, Ann Arbor, MI 48109 (J.H.E., N.E.C., S.D.K., M.S.D.); Department of Radiology, New York University Langone Medical Center, New York, NY (N.M.H., H.C.); Department of Radiology, University of Ottawa, Ottawa, Canada (N.S.); Department of Radiology, University of Alabama School of Medicine, Birmingham, Ala (A.D.S.); Imaging Institute and Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio (E.M.R.); Department of Radiology, David Geffen School of Medicine, UCLA Center for the Health Sciences, Los Angeles, Calif (S.S.R.); Department of Radiology, University of Wisconsin Hospital and Clinics, Madison, Wis (S.A.W.); and Department of Radiology, UCSF Medical Center, San Francisco, Calif (Z.J.W.)
| | - Atul B Shinagare
- From the Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (S.G.S., A.B.S.); Disease-Focused Panel on Renal Cell Carcinoma, Society of Abdominal Radiology, Houston, Tex (S.G.S., I.P., N.M.H., N.S., A.D.S., E.M.R., A.B.S., N.E.C., S.S.R., S.A.W., S.D.K., Z.J.W., H.C., M.S.D.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); Departments of Radiology and Urology, Michigan Medicine, University of Michigan, 1500 E Medical Center Dr, B2-A209A, Ann Arbor, MI 48109 (J.H.E., N.E.C., S.D.K., M.S.D.); Department of Radiology, New York University Langone Medical Center, New York, NY (N.M.H., H.C.); Department of Radiology, University of Ottawa, Ottawa, Canada (N.S.); Department of Radiology, University of Alabama School of Medicine, Birmingham, Ala (A.D.S.); Imaging Institute and Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio (E.M.R.); Department of Radiology, David Geffen School of Medicine, UCLA Center for the Health Sciences, Los Angeles, Calif (S.S.R.); Department of Radiology, University of Wisconsin Hospital and Clinics, Madison, Wis (S.A.W.); and Department of Radiology, UCSF Medical Center, San Francisco, Calif (Z.J.W.)
| | - Nicole E Curci
- From the Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (S.G.S., A.B.S.); Disease-Focused Panel on Renal Cell Carcinoma, Society of Abdominal Radiology, Houston, Tex (S.G.S., I.P., N.M.H., N.S., A.D.S., E.M.R., A.B.S., N.E.C., S.S.R., S.A.W., S.D.K., Z.J.W., H.C., M.S.D.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); Departments of Radiology and Urology, Michigan Medicine, University of Michigan, 1500 E Medical Center Dr, B2-A209A, Ann Arbor, MI 48109 (J.H.E., N.E.C., S.D.K., M.S.D.); Department of Radiology, New York University Langone Medical Center, New York, NY (N.M.H., H.C.); Department of Radiology, University of Ottawa, Ottawa, Canada (N.S.); Department of Radiology, University of Alabama School of Medicine, Birmingham, Ala (A.D.S.); Imaging Institute and Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio (E.M.R.); Department of Radiology, David Geffen School of Medicine, UCLA Center for the Health Sciences, Los Angeles, Calif (S.S.R.); Department of Radiology, University of Wisconsin Hospital and Clinics, Madison, Wis (S.A.W.); and Department of Radiology, UCSF Medical Center, San Francisco, Calif (Z.J.W.)
| | - Steven S Raman
- From the Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (S.G.S., A.B.S.); Disease-Focused Panel on Renal Cell Carcinoma, Society of Abdominal Radiology, Houston, Tex (S.G.S., I.P., N.M.H., N.S., A.D.S., E.M.R., A.B.S., N.E.C., S.S.R., S.A.W., S.D.K., Z.J.W., H.C., M.S.D.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); Departments of Radiology and Urology, Michigan Medicine, University of Michigan, 1500 E Medical Center Dr, B2-A209A, Ann Arbor, MI 48109 (J.H.E., N.E.C., S.D.K., M.S.D.); Department of Radiology, New York University Langone Medical Center, New York, NY (N.M.H., H.C.); Department of Radiology, University of Ottawa, Ottawa, Canada (N.S.); Department of Radiology, University of Alabama School of Medicine, Birmingham, Ala (A.D.S.); Imaging Institute and Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio (E.M.R.); Department of Radiology, David Geffen School of Medicine, UCLA Center for the Health Sciences, Los Angeles, Calif (S.S.R.); Department of Radiology, University of Wisconsin Hospital and Clinics, Madison, Wis (S.A.W.); and Department of Radiology, UCSF Medical Center, San Francisco, Calif (Z.J.W.)
| | - Shane A Wells
- From the Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (S.G.S., A.B.S.); Disease-Focused Panel on Renal Cell Carcinoma, Society of Abdominal Radiology, Houston, Tex (S.G.S., I.P., N.M.H., N.S., A.D.S., E.M.R., A.B.S., N.E.C., S.S.R., S.A.W., S.D.K., Z.J.W., H.C., M.S.D.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); Departments of Radiology and Urology, Michigan Medicine, University of Michigan, 1500 E Medical Center Dr, B2-A209A, Ann Arbor, MI 48109 (J.H.E., N.E.C., S.D.K., M.S.D.); Department of Radiology, New York University Langone Medical Center, New York, NY (N.M.H., H.C.); Department of Radiology, University of Ottawa, Ottawa, Canada (N.S.); Department of Radiology, University of Alabama School of Medicine, Birmingham, Ala (A.D.S.); Imaging Institute and Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio (E.M.R.); Department of Radiology, David Geffen School of Medicine, UCLA Center for the Health Sciences, Los Angeles, Calif (S.S.R.); Department of Radiology, University of Wisconsin Hospital and Clinics, Madison, Wis (S.A.W.); and Department of Radiology, UCSF Medical Center, San Francisco, Calif (Z.J.W.)
| | - Samuel D Kaffenberger
- From the Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (S.G.S., A.B.S.); Disease-Focused Panel on Renal Cell Carcinoma, Society of Abdominal Radiology, Houston, Tex (S.G.S., I.P., N.M.H., N.S., A.D.S., E.M.R., A.B.S., N.E.C., S.S.R., S.A.W., S.D.K., Z.J.W., H.C., M.S.D.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); Departments of Radiology and Urology, Michigan Medicine, University of Michigan, 1500 E Medical Center Dr, B2-A209A, Ann Arbor, MI 48109 (J.H.E., N.E.C., S.D.K., M.S.D.); Department of Radiology, New York University Langone Medical Center, New York, NY (N.M.H., H.C.); Department of Radiology, University of Ottawa, Ottawa, Canada (N.S.); Department of Radiology, University of Alabama School of Medicine, Birmingham, Ala (A.D.S.); Imaging Institute and Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio (E.M.R.); Department of Radiology, David Geffen School of Medicine, UCLA Center for the Health Sciences, Los Angeles, Calif (S.S.R.); Department of Radiology, University of Wisconsin Hospital and Clinics, Madison, Wis (S.A.W.); and Department of Radiology, UCSF Medical Center, San Francisco, Calif (Z.J.W.)
| | - Zhen J Wang
- From the Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (S.G.S., A.B.S.); Disease-Focused Panel on Renal Cell Carcinoma, Society of Abdominal Radiology, Houston, Tex (S.G.S., I.P., N.M.H., N.S., A.D.S., E.M.R., A.B.S., N.E.C., S.S.R., S.A.W., S.D.K., Z.J.W., H.C., M.S.D.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); Departments of Radiology and Urology, Michigan Medicine, University of Michigan, 1500 E Medical Center Dr, B2-A209A, Ann Arbor, MI 48109 (J.H.E., N.E.C., S.D.K., M.S.D.); Department of Radiology, New York University Langone Medical Center, New York, NY (N.M.H., H.C.); Department of Radiology, University of Ottawa, Ottawa, Canada (N.S.); Department of Radiology, University of Alabama School of Medicine, Birmingham, Ala (A.D.S.); Imaging Institute and Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio (E.M.R.); Department of Radiology, David Geffen School of Medicine, UCLA Center for the Health Sciences, Los Angeles, Calif (S.S.R.); Department of Radiology, University of Wisconsin Hospital and Clinics, Madison, Wis (S.A.W.); and Department of Radiology, UCSF Medical Center, San Francisco, Calif (Z.J.W.)
| | - Hersh Chandarana
- From the Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (S.G.S., A.B.S.); Disease-Focused Panel on Renal Cell Carcinoma, Society of Abdominal Radiology, Houston, Tex (S.G.S., I.P., N.M.H., N.S., A.D.S., E.M.R., A.B.S., N.E.C., S.S.R., S.A.W., S.D.K., Z.J.W., H.C., M.S.D.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); Departments of Radiology and Urology, Michigan Medicine, University of Michigan, 1500 E Medical Center Dr, B2-A209A, Ann Arbor, MI 48109 (J.H.E., N.E.C., S.D.K., M.S.D.); Department of Radiology, New York University Langone Medical Center, New York, NY (N.M.H., H.C.); Department of Radiology, University of Ottawa, Ottawa, Canada (N.S.); Department of Radiology, University of Alabama School of Medicine, Birmingham, Ala (A.D.S.); Imaging Institute and Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio (E.M.R.); Department of Radiology, David Geffen School of Medicine, UCLA Center for the Health Sciences, Los Angeles, Calif (S.S.R.); Department of Radiology, University of Wisconsin Hospital and Clinics, Madison, Wis (S.A.W.); and Department of Radiology, UCSF Medical Center, San Francisco, Calif (Z.J.W.)
| | - Matthew S Davenport
- From the Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (S.G.S., A.B.S.); Disease-Focused Panel on Renal Cell Carcinoma, Society of Abdominal Radiology, Houston, Tex (S.G.S., I.P., N.M.H., N.S., A.D.S., E.M.R., A.B.S., N.E.C., S.S.R., S.A.W., S.D.K., Z.J.W., H.C., M.S.D.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); Departments of Radiology and Urology, Michigan Medicine, University of Michigan, 1500 E Medical Center Dr, B2-A209A, Ann Arbor, MI 48109 (J.H.E., N.E.C., S.D.K., M.S.D.); Department of Radiology, New York University Langone Medical Center, New York, NY (N.M.H., H.C.); Department of Radiology, University of Ottawa, Ottawa, Canada (N.S.); Department of Radiology, University of Alabama School of Medicine, Birmingham, Ala (A.D.S.); Imaging Institute and Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio (E.M.R.); Department of Radiology, David Geffen School of Medicine, UCLA Center for the Health Sciences, Los Angeles, Calif (S.S.R.); Department of Radiology, University of Wisconsin Hospital and Clinics, Madison, Wis (S.A.W.); and Department of Radiology, UCSF Medical Center, San Francisco, Calif (Z.J.W.)
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Abstract
OBJECTIVE. Renal masses comprise a heterogeneous group of pathologic conditions, including benign and indolent diseases and aggressive malignancies, complicating management. In this article, we explore the emerging role of imaging to provide a comprehensive noninvasive characterization of a renal mass-so-called "virtual biopsy"-and its potential use in the management of patients with renal tumors. CONCLUSION. Percutaneous renal mass biopsy (RMB) remains a valuable method to provide a presurgical histopathologic diagnosis of renal masses, but it is an invasive procedure and is not always feasible. Accumulating data support the use of imaging features to predict histopathology of renal masses. Imaging may help address some of the inherent limitations of RMB, and in certain settings, a multimodal clinical approach may allow decreasing the need for RMB.
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Vogel C, Ziegelmüller B, Ljungberg B, Bensalah K, Bex A, Canfield S, Giles RH, Hora M, Kuczyk MA, Merseburger AS, Powles T, Albiges L, Stewart F, Volpe A, Graser A, Schlemmer M, Yuan C, Lam T, Staehler M. Imaging in Suspected Renal-Cell Carcinoma: Systematic Review. Clin Genitourin Cancer 2019; 17:e345-e355. [DOI: 10.1016/j.clgc.2018.07.024] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2017] [Revised: 07/08/2018] [Accepted: 07/30/2018] [Indexed: 01/14/2023]
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Kang SK, Huang WC, Elkin EB, Pandharipande PV, Braithwaite RS. Personalized Treatment for Small Renal Tumors: Decision Analysis of Competing Causes of Mortality. Radiology 2019; 290:732-743. [PMID: 30644815 PMCID: PMC6394736 DOI: 10.1148/radiol.2018181114] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2018] [Revised: 11/21/2018] [Accepted: 11/23/2018] [Indexed: 12/29/2022]
Abstract
Purpose To compare the effectiveness of personalized treatment for small (≤4 cm) renal tumors versus routine partial nephrectomy (PN), accounting for various competing causes of mortality. Materials and Methods A state-transition microsimulation model was constructed to compare life expectancy of management strategies for small renal tumors by using 1 000 000 simulations in the following ways: routine PN or personalized treatment involving percutaneous ablation for risk factors for worsening chronic kidney disease (CKD), and otherwise PN; biopsy, with triage of renal cell carcinoma (RCC) to PN or ablation depending on risk factors for worsening CKD; active surveillance for growth; and active surveillance when MRI findings are indicative of papillary RCC. Transition probabilities were incorporated from the literature. Effects of parameter variability were assessed in sensitivity analysis. Results In patients of all ages with normal renal function, routine PN yielded the longest life expectancy (eg, 0.67 years in 65-year-old men with nephrometry score [NS] of 4). Otherwise, personalized strategies extended life expectancy versus routine PN: in CKD stages 2 or 3a, moderate or high NS, and no comorbidities, MRI guidance for active surveillance extended life expectancy (eg, 2.60 years for MRI vs PN in CKD 3a, NS 10); and with Charlson comorbidity index of 1 or more, biopsy or active surveillance for growth extended life expectancy (eg, 2.70 years for surveillance for growth in CKD 3a, NS 10). CKD 3b was most effectively managed by using MRI to help predict papillary RCC for surveillance. Conclusion For patients with chronic kidney disease and small renal tumors, personalized treatment selection likely extends life expectancy. © RSNA, 2019 Online supplemental material is available for this article.
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Affiliation(s)
- Stella K. Kang
- From the Departments of Radiology (S.K.K.), Population Health (S.K.K., R.S.B.), Urology (W.C.H.), and Medicine (R.S.B.), NYU School of Medicine, 550 First Ave, New York, NY 10016; Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, NY (E.B.E.); and Institute for Technology Assessment and Department of Radiology, Massachusetts General Hospital, Boston, Mass (P.V.P.)
| | - William C. Huang
- From the Departments of Radiology (S.K.K.), Population Health (S.K.K., R.S.B.), Urology (W.C.H.), and Medicine (R.S.B.), NYU School of Medicine, 550 First Ave, New York, NY 10016; Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, NY (E.B.E.); and Institute for Technology Assessment and Department of Radiology, Massachusetts General Hospital, Boston, Mass (P.V.P.)
| | - Elena B. Elkin
- From the Departments of Radiology (S.K.K.), Population Health (S.K.K., R.S.B.), Urology (W.C.H.), and Medicine (R.S.B.), NYU School of Medicine, 550 First Ave, New York, NY 10016; Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, NY (E.B.E.); and Institute for Technology Assessment and Department of Radiology, Massachusetts General Hospital, Boston, Mass (P.V.P.)
| | - Pari V. Pandharipande
- From the Departments of Radiology (S.K.K.), Population Health (S.K.K., R.S.B.), Urology (W.C.H.), and Medicine (R.S.B.), NYU School of Medicine, 550 First Ave, New York, NY 10016; Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, NY (E.B.E.); and Institute for Technology Assessment and Department of Radiology, Massachusetts General Hospital, Boston, Mass (P.V.P.)
| | - R. Scott Braithwaite
- From the Departments of Radiology (S.K.K.), Population Health (S.K.K., R.S.B.), Urology (W.C.H.), and Medicine (R.S.B.), NYU School of Medicine, 550 First Ave, New York, NY 10016; Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, NY (E.B.E.); and Institute for Technology Assessment and Department of Radiology, Massachusetts General Hospital, Boston, Mass (P.V.P.)
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Abstract
New developments in cross-sectional imaging, including contrast-enhanced ultrasound, dual-energy computed tomography, multiparametric magnetic resonance imaging, single-photon emission computed tomography, and positron emission tomography, together with novel application of existing and novel radiotracers, have changed the landscape of renal mass characterization (ie, virtual biopsy) as well as the detection of metastatic disease, prognostication, and response assessment in patients with advanced kidney cancer. A host of imaging response criteria have been developed to characterize the response to targeted and immune therapies and correlate with patient outcomes, each with strengths and limitations. Recent efforts to advance the field are aimed at increasing objectivity with quantitative techniques and the use of banks of imaging data to match the vast genomic data that are becoming available. The emerging field of radiogenomics has the potential to transform further the role of imaging in kidney cancer management through eventual noninvasive characterization of the tumor histology and genetic microenvironment in single renal masses and/or metastatic disease. We review of the effect of currently available imaging techniques in the management of patients with kidney cancer, including localized, locally advanced, and metastatic disease.
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Affiliation(s)
- Katherine M. Krajewski
- Katherine M. Krajewski, Harvard Medical School, Boston, MA; and Ivan Pedrosa, University of Texas Southwestern Medical Center, Dallas, TX
| | - Ivan Pedrosa
- Katherine M. Krajewski, Harvard Medical School, Boston, MA; and Ivan Pedrosa, University of Texas Southwestern Medical Center, Dallas, TX
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Chiarello MA, Mali RD, Kang SK. Diagnostic Accuracy of MRI for Detection of Papillary Renal Cell Carcinoma: A Systematic Review and Meta-Analysis. AJR Am J Roentgenol 2018; 211:812-821. [PMID: 30063398 PMCID: PMC6440798 DOI: 10.2214/ajr.17.19462] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
OBJECTIVE The objective of our study was to perform a systematic review and meta-analysis of the diagnostic performance of MRI in differentiation of papillary renal cell carcinoma (RCC) from other renal masses. MATERIALS AND METHODS We performed searches of three electronic databases for studies that used MRI techniques to differentiate papillary RCC from other renal lesions. Methodologic quality was assessed, and diagnostic test accuracy was summarized using bivariate random-effects modeling or with construction of a summary ROC (SROC) curve. RESULTS Thirteen studies involving 275 papillary RCC lesions and 758 other renal masses met the inclusion criteria. Resulting summary estimates for the performance of MRI to differentiate papillary RCC from other renal lesions were a sensitivity of 79.6% (95% CI, 62.3-90.2%) and specificity of 88.1% (95% CI, 80.1-93.1%). In subgroup analysis, quantitative pooling of seven studies using enhancement in the corticomedullary phase resulted in a sensitivity of 85.6% (95% CI, 67.8-94.4%), specificity of 91.7% (95% CI, 76.0-97.5%), and area under the SROC curve of 0.894. Four studies used tumor appearance on T2-weighted imaging to detect papillary RCC, and results showed a pooled sensitivity of 89.9% (95% CI, 73.0-96.7%) and specificity of 84.9% (95% CI, 69.0-93.4%). Three studies used signal loss on T1-weighted in-phase imaging to detect papillary RCC but marked heterogeneity precluded pooling. CONCLUSION Meta-analysis supports moderate sensitivity and excellent specificity of quantitative enhancement in the corticomedullary phase for differentiating papillary RCC from other tumors. The accuracy of combining enhancement and T2 signal-intensity characteristics merits further evaluation as a potential aid for management decisions.
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Affiliation(s)
- Matthew A Chiarello
- 1 Department of Radiology, NYU School of Medicine, 550 First Ave, New York, NY 10016
| | - Rahul D Mali
- 1 Department of Radiology, NYU School of Medicine, 550 First Ave, New York, NY 10016
| | - Stella K Kang
- 1 Department of Radiology, NYU School of Medicine, 550 First Ave, New York, NY 10016
- 2 Department of Population Health, NYU School of Medicine, New York, NY
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Abstract
PURPOSE OF REVIEW To review the growth kinetics of small renal masses and available imaging modalities for mass characterization and surveillance, highlight current organizational recommendations for the active surveillance of small renal masses, and discuss the most recently reported oncological outcomes of patients as they relate to various surveillance imaging protocols and progression to delayed intervention. RECENT FINDINGS Overall, organizational guideline recommendations are broad and lack specifics regarding timing and modality for follow-up imaging of small renal masses. Additionally, despite general consensus in the literature about certain criteria to trigger delayed intervention, there exist no formal guidelines. Active surveillance of small renal masses is an acceptable management strategy for patients with prohibitive surgical risk; however, standardized imaging protocols for surveillance are lacking, as are randomized, prospective trials to evaluate the ideal follow-up protocol.
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32
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Abstract
The increase in serendipitous detection of solid renal masses on imaging has not resulted in a reduction in mortality from renal cell carcinoma. Consequently, efforts for improved lesion characterization have been pursued and incorporated into management algorithms for distinguishing clinically significant tumors from those with favorable histology or benign conditions. Although diagnostic imaging strategies have evolved for optimized lesion detection, distinction between benign tumors and both indolent and aggressive malignant neoplasms remain an important diagnostic challenge. Recent advances in cross-sectional imaging have expanded the role of these tests in the noninvasive characterization of solid renal tumors.
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Affiliation(s)
- Fernando U Kay
- Department of Radiology; UT Southwestern Medical Center, 2201 Inwood Road, Suite 210, Dallas, TX 75390, USA
| | - Ivan Pedrosa
- Department of Radiology; UT Southwestern Medical Center, 2201 Inwood Road, Suite 210, Dallas, TX 75390, USA.
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Scharitzer M, Tamandl D, Ba-Ssalamah A. [Incidental findings of the kidneys, adrenal glands, adnexa uteri, gastrointestinal tract, mesentery and lymph nodes : Assessment and management recommendations]. Radiologe 2018; 57:279-285. [PMID: 28283731 DOI: 10.1007/s00117-017-0236-9] [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: 10/20/2022]
Abstract
CLINICAL ISSUE Besides the upper abdominal parenchymal organs, the increasing application of cross-sectional imaging has also led to a rising number of incidental findings in the kidneys, adrenal glands, adnexa uteri, the gastrointestinal tract, mesentery and abdominal lymph nodes. STANDARD RADIOLOGICAL METHODS Abdominal computed tomography investigations often show unexpected findings without any correlating symptoms. The growing clinical relevance is due to the large number of incidental findings as well as an increasing awareness of ethical and socioeconomic factors. ACHIEVEMENTS When interpreting radiological findings not only morphological criteria but also individual risk factors of the patient and the clinical context are of great importance. PRACTICAL RECOMMENDATIONS The aims of this article are the description and evaluation of frequent incidental findings detected by computed tomography and to provide information about management recommendations.
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Affiliation(s)
- M Scharitzer
- Universitätsklinik für Radiologie und Nuklearmedizin, Medizinische Universität Wien, Währinger Gürtel 18-20, 1090, Wien, Österreich.
| | - D Tamandl
- Universitätsklinik für Radiologie und Nuklearmedizin, Medizinische Universität Wien, Währinger Gürtel 18-20, 1090, Wien, Österreich
| | - A Ba-Ssalamah
- Universitätsklinik für Radiologie und Nuklearmedizin, Medizinische Universität Wien, Währinger Gürtel 18-20, 1090, Wien, Österreich
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Schieda N, Lim RS, McInnes MDF, Thomassin I, Renard-Penna R, Tavolaro S, Cornelis FH. Characterization of small (<4cm) solid renal masses by computed tomography and magnetic resonance imaging: Current evidence and further development. Diagn Interv Imaging 2018; 99:443-455. [PMID: 29606371 DOI: 10.1016/j.diii.2018.03.004] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2018] [Accepted: 03/07/2018] [Indexed: 12/15/2022]
Abstract
Diagnosis of renal cell carcinomas (RCC) subtypes on computed tomography (CT) and magnetic resonance imaging (MRI) is clinically important. There is increased evidence that confident imaging diagnosis is now possible while standardization of the protocols is still required. Fat-poor angiomyolipoma show homogeneously increased unenhanced attenuation, homogeneously low signal on T2-weighted MRI and apparent diffusion coefficient (ADC) map, may contain microscopic fat and are classically avidly enhancing. Papillary RCC are also typically hyperattenuating and of low signal on T2-weighted MRI and ADC map; however, their gradual progressive enhancement after intravenous administration of contrast material is a differentiating feature. Clear cell RCC are avidly enhancing and may show intracellular lipid; however, these tumors are heterogeneous and are of characteristically increased signal on T2-weighted MRI. Oncocytomas and chromophobe tumors (collectively oncocytic neoplasms) show intermediate imaging findings on CT and MRI and are the most difficult subtype to characterize accurately; however, both show intermediately increased signal on T2-weighted with more gradual enhancement compared to clear cell RCC. Chromophobe tumors tend to be more homogeneous compared to oncocytomas, which can be heterogeneous, but other described features (e.g. scar, segmental enhancement inversion) overlap considerably between tumors. Tumor grade is another important consideration in small solid renal masses with emerging studies on both CT and MRI suggesting that high grade tumors may be separated from lower grade disease based upon imaging features.
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Affiliation(s)
- N Schieda
- Department of Medical Imaging, The Ottawa Hospital, The University of Ottawa, Ottawa, ON, Canada
| | - R S Lim
- Department of Medical Imaging, The Ottawa Hospital, The University of Ottawa, Ottawa, ON, Canada
| | - M D F McInnes
- Department of Medical Imaging, The Ottawa Hospital, The University of Ottawa, Ottawa, ON, Canada
| | - I Thomassin
- Sorbonne Université, Institut des Sciences du Calcul et des Données, Department of Radiology, Tenon Hospital - HUEP - APHP, 4 rue de la Chine, 75020 Paris, France
| | - R Renard-Penna
- Sorbonne Université, Institut des Sciences du Calcul et des Données, Department of Radiology, Tenon Hospital - HUEP - APHP, 4 rue de la Chine, 75020 Paris, France
| | - S Tavolaro
- Sorbonne Université, Institut des Sciences du Calcul et des Données, Department of Radiology, Tenon Hospital - HUEP - APHP, 4 rue de la Chine, 75020 Paris, France
| | - F H Cornelis
- Sorbonne Université, Institut des Sciences du Calcul et des Données, Department of Radiology, Tenon Hospital - HUEP - APHP, 4 rue de la Chine, 75020 Paris, France.
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35
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Abstract
PURPOSE OF REVIEW Renal cell carcinoma is a heterogeneous disease with a spectrum of subtypes and clinical behavior. Quantitative and qualitative imaging biomarkers are sought to correlate with genetic and histologic features and complement pathologic analysis. RECENT FINDINGS Texture analysis, radiogenomics, and modality-specific advancements have yielded an array of renal cell carcinoma imaging biomarkers in the research domain. Although many techniques are promising, standardization and validation of these procedures are needed prior to implementation into clinical practice. SUMMARY We introduce novel imaging techniques and analytic methods which have been shown to contribute to characterization of renal cell carcinoma and its subtypes, aggressiveness, and responsiveness to therapy, including associated advantages and limitations.
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Kay FU, Canvasser NE, Xi Y, Pinho DF, Costa DN, Diaz de Leon A, Khatri G, Leyendecker JR, Yokoo T, Lay AH, Kavoussi N, Koseoglu E, Cadeddu JA, Pedrosa I. Diagnostic Performance and Interreader Agreement of a Standardized MR Imaging Approach in the Prediction of Small Renal Mass Histology. Radiology 2018; 287:543-553. [PMID: 29390196 DOI: 10.1148/radiol.2018171557] [Citation(s) in RCA: 64] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Purpose To assess the diagnostic performance and interreader agreement of a standardized diagnostic algorithm in determining the histologic type of small (≤4 cm) renal masses (SRMs) with multiparametric magnetic resonance (MR) imaging. Materials and Methods This single-center retrospective HIPAA-compliant institutional review board-approved study included 103 patients with 109 SRMs resected between December 2011 and July 2015. The requirement for informed consent was waived. Presurgical renal MR images were reviewed by seven radiologists with diverse experience. Eleven MR imaging features were assessed, and a standardized diagnostic algorithm was used to determine the most likely histologic diagnosis, which was compared with histopathology results after surgery. Interreader variability was tested with the Cohen κ statistic. Regression models using MR imaging features were used to predict the histopathologic diagnosis with 5% significance level. Results Clear cell renal cell carcinoma (RCC) and papillary RCC were diagnosed, with sensitivities of 85% (47 of 55) and 80% (20 of 25), respectively, and specificities of 76% (41 of 54) and 94% (79 of 84), respectively. Interreader agreement was moderate to substantial (clear cell RCC, κ = 0.58; papillary RCC, κ = 0.73). Signal intensity (SI) of the lesion on T2-weighted MR images and degree of contrast enhancement (CE) during the corticomedullary phase were independent predictors of clear cell RCC (SI odds ratio [OR]: 3.19; 95% confidence interval [CI]: 1.4, 7.1; P = .003; CE OR, 4.45; 95% CI: 1.8, 10.8; P < .001) and papillary RCC (CE OR, 0.053; 95% CI: 0.02, 0.2; P < .001), and both had substantial interreader agreement (SI, κ = 0.69; CE, κ = 0.71). Poorer performance was observed for chromophobe histology, oncocytomas, and minimal fat angiomyolipomas, (sensitivity range, 14%-67%; specificity range, 97%-99%), with fair to moderate interreader agreement (κ range = 0.23-0.43). Segmental enhancement inversion was an independent predictor of oncocytomas (OR, 16.21; 95% CI: 1.0, 275.4; P = .049), with moderate interreader agreement (κ = 0.49). Conclusion The proposed standardized MR imaging-based diagnostic algorithm had diagnostic accuracy of 81% (88 of 109) and 91% (99 of 109) in the diagnosis of clear cell RCC and papillary RCC, respectively, while achieving moderate to substantial interreader agreement among seven radiologists. © RSNA, 2018 Online supplemental material is available for this article.
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Affiliation(s)
- Fernando U Kay
- From the Department of Radiology (F.U.K., Y.X., D.F.P., D.N.C., A.D.d.L., G.K., J.R.L., T.Y., J.A.C., I.P.), Department of Urology (N.E.C., A.H.L., N.K., E.K., J.A.C., I.P.), and Advanced Imaging Research Center (D.C., T.Y., I.P.), University of Texas Southwestern Medical Center, 2201 Inwood Rd, Suite NE2.210, Dallas, TX 75390-9085
| | - Noah E Canvasser
- From the Department of Radiology (F.U.K., Y.X., D.F.P., D.N.C., A.D.d.L., G.K., J.R.L., T.Y., J.A.C., I.P.), Department of Urology (N.E.C., A.H.L., N.K., E.K., J.A.C., I.P.), and Advanced Imaging Research Center (D.C., T.Y., I.P.), University of Texas Southwestern Medical Center, 2201 Inwood Rd, Suite NE2.210, Dallas, TX 75390-9085
| | - Yin Xi
- From the Department of Radiology (F.U.K., Y.X., D.F.P., D.N.C., A.D.d.L., G.K., J.R.L., T.Y., J.A.C., I.P.), Department of Urology (N.E.C., A.H.L., N.K., E.K., J.A.C., I.P.), and Advanced Imaging Research Center (D.C., T.Y., I.P.), University of Texas Southwestern Medical Center, 2201 Inwood Rd, Suite NE2.210, Dallas, TX 75390-9085
| | - Daniella F Pinho
- From the Department of Radiology (F.U.K., Y.X., D.F.P., D.N.C., A.D.d.L., G.K., J.R.L., T.Y., J.A.C., I.P.), Department of Urology (N.E.C., A.H.L., N.K., E.K., J.A.C., I.P.), and Advanced Imaging Research Center (D.C., T.Y., I.P.), University of Texas Southwestern Medical Center, 2201 Inwood Rd, Suite NE2.210, Dallas, TX 75390-9085
| | - Daniel N Costa
- From the Department of Radiology (F.U.K., Y.X., D.F.P., D.N.C., A.D.d.L., G.K., J.R.L., T.Y., J.A.C., I.P.), Department of Urology (N.E.C., A.H.L., N.K., E.K., J.A.C., I.P.), and Advanced Imaging Research Center (D.C., T.Y., I.P.), University of Texas Southwestern Medical Center, 2201 Inwood Rd, Suite NE2.210, Dallas, TX 75390-9085
| | - Alberto Diaz de Leon
- From the Department of Radiology (F.U.K., Y.X., D.F.P., D.N.C., A.D.d.L., G.K., J.R.L., T.Y., J.A.C., I.P.), Department of Urology (N.E.C., A.H.L., N.K., E.K., J.A.C., I.P.), and Advanced Imaging Research Center (D.C., T.Y., I.P.), University of Texas Southwestern Medical Center, 2201 Inwood Rd, Suite NE2.210, Dallas, TX 75390-9085
| | - Gaurav Khatri
- From the Department of Radiology (F.U.K., Y.X., D.F.P., D.N.C., A.D.d.L., G.K., J.R.L., T.Y., J.A.C., I.P.), Department of Urology (N.E.C., A.H.L., N.K., E.K., J.A.C., I.P.), and Advanced Imaging Research Center (D.C., T.Y., I.P.), University of Texas Southwestern Medical Center, 2201 Inwood Rd, Suite NE2.210, Dallas, TX 75390-9085
| | - John R Leyendecker
- From the Department of Radiology (F.U.K., Y.X., D.F.P., D.N.C., A.D.d.L., G.K., J.R.L., T.Y., J.A.C., I.P.), Department of Urology (N.E.C., A.H.L., N.K., E.K., J.A.C., I.P.), and Advanced Imaging Research Center (D.C., T.Y., I.P.), University of Texas Southwestern Medical Center, 2201 Inwood Rd, Suite NE2.210, Dallas, TX 75390-9085
| | - Takeshi Yokoo
- From the Department of Radiology (F.U.K., Y.X., D.F.P., D.N.C., A.D.d.L., G.K., J.R.L., T.Y., J.A.C., I.P.), Department of Urology (N.E.C., A.H.L., N.K., E.K., J.A.C., I.P.), and Advanced Imaging Research Center (D.C., T.Y., I.P.), University of Texas Southwestern Medical Center, 2201 Inwood Rd, Suite NE2.210, Dallas, TX 75390-9085
| | - Aaron H Lay
- From the Department of Radiology (F.U.K., Y.X., D.F.P., D.N.C., A.D.d.L., G.K., J.R.L., T.Y., J.A.C., I.P.), Department of Urology (N.E.C., A.H.L., N.K., E.K., J.A.C., I.P.), and Advanced Imaging Research Center (D.C., T.Y., I.P.), University of Texas Southwestern Medical Center, 2201 Inwood Rd, Suite NE2.210, Dallas, TX 75390-9085
| | - Nicholas Kavoussi
- From the Department of Radiology (F.U.K., Y.X., D.F.P., D.N.C., A.D.d.L., G.K., J.R.L., T.Y., J.A.C., I.P.), Department of Urology (N.E.C., A.H.L., N.K., E.K., J.A.C., I.P.), and Advanced Imaging Research Center (D.C., T.Y., I.P.), University of Texas Southwestern Medical Center, 2201 Inwood Rd, Suite NE2.210, Dallas, TX 75390-9085
| | - Ersin Koseoglu
- From the Department of Radiology (F.U.K., Y.X., D.F.P., D.N.C., A.D.d.L., G.K., J.R.L., T.Y., J.A.C., I.P.), Department of Urology (N.E.C., A.H.L., N.K., E.K., J.A.C., I.P.), and Advanced Imaging Research Center (D.C., T.Y., I.P.), University of Texas Southwestern Medical Center, 2201 Inwood Rd, Suite NE2.210, Dallas, TX 75390-9085
| | - Jeffrey A Cadeddu
- From the Department of Radiology (F.U.K., Y.X., D.F.P., D.N.C., A.D.d.L., G.K., J.R.L., T.Y., J.A.C., I.P.), Department of Urology (N.E.C., A.H.L., N.K., E.K., J.A.C., I.P.), and Advanced Imaging Research Center (D.C., T.Y., I.P.), University of Texas Southwestern Medical Center, 2201 Inwood Rd, Suite NE2.210, Dallas, TX 75390-9085
| | - Ivan Pedrosa
- From the Department of Radiology (F.U.K., Y.X., D.F.P., D.N.C., A.D.d.L., G.K., J.R.L., T.Y., J.A.C., I.P.), Department of Urology (N.E.C., A.H.L., N.K., E.K., J.A.C., I.P.), and Advanced Imaging Research Center (D.C., T.Y., I.P.), University of Texas Southwestern Medical Center, 2201 Inwood Rd, Suite NE2.210, Dallas, TX 75390-9085
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Chemical shift magnetic resonance imaging for distinguishing minimal-fat renal angiomyolipoma from renal cell carcinoma: a meta-analysis. Eur Radiol 2017; 28:1854-1861. [PMID: 29178029 DOI: 10.1007/s00330-017-5141-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2017] [Revised: 10/07/2017] [Accepted: 10/17/2017] [Indexed: 12/28/2022]
Abstract
OBJECTIVES To determine the performance of chemical shift signal intensity index (CS-SII) values for distinguishing minimal-fat renal angiomyolipoma (mfAML) from renal cell carcinoma (RCC) and to assess RCC subtype characterisation. METHODS We identified eligible studies on CS magnetic resonance imaging (CS-MRI) of focal renal lesions via PubMed, Embase, and the Cochrane Library. CS-SII values were extracted by lesion type and evaluated using linear mixed model-based meta-regression. RCC subtypes were analysed. Two-sided p value <0.05 indicated statistical significance. Methodological quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 tool. RESULTS Eleven articles involving 850 patients were included. Minimal-fat AML had significantly higher CS-SII value than RCC (p < 0.05); there were no significant differences between mfAML and clear cell RCC (cc-RCC) (p = 0.112). Clear cell RCC had a significantly higher CS-SII value than papillary RCC (p-RCC) (p < 0.001) and chromophobe RCC (ch-RCC) (p = 0.045). The methodological quality was relatively high, and Begg's test data points indicated no obvious publication bias. CONCLUSIONS The CS-SII value for differentiating mfAML from cc-RCC remains unproven, but is a promising method for differentiating cc-RCC from p-RCC and ch-RCC. KEY POINTS • RCC CS-SII values are significantly lower than those of mfAML overall. • CS-SII values cannot aid differentiation between mfAML and cc-RCC. • CS-SII values might help characterise RCC subtypes.
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Abstract
Renal cell carcinoma (RCC) exhibits a diverse and heterogeneous disease spectrum, but insight into its molecular biology has provided an improved understanding of potential risk factors, oncologic behavior, and imaging features. Computed tomography (CT) and MR imaging may allow the identification and preoperative subtyping of RCC and assessment of a response to various therapies. Active surveillance is a viable management option in some patients and has provided further insight into the natural history of RCC, including the favorable prognosis of cystic neoplasms. This article reviews CT and MR imaging in RCC and the role of screening in selected high-risk populations.
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Affiliation(s)
- Alberto Diaz de Leon
- Department of Radiology, University of Texas Southwestern Medical Center, 2201 Inwood Road, 2nd Floor, Suite 202, Dallas, TX 75390-9085, USA
| | - Ivan Pedrosa
- Department of Radiology, University of Texas Southwestern Medical Center, 2201 Inwood Road, 2nd Floor, Suite 202, Dallas, TX 75390-9085, USA.
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Zhang Y, Udayakumar D, Cai L, Hu Z, Kapur P, Kho EY, Pavía-Jiménez A, Fulkerson M, de Leon AD, Yuan Q, Dimitrov IE, Yokoo T, Ye J, Mitsche MA, Kim H, McDonald JG, Xi Y, Madhuranthakam AJ, Dwivedi DK, Lenkinski RE, Cadeddu JA, Margulis V, Brugarolas J, DeBerardinis RJ, Pedrosa I. Addressing metabolic heterogeneity in clear cell renal cell carcinoma with quantitative Dixon MRI. JCI Insight 2017; 2:94278. [PMID: 28768909 DOI: 10.1172/jci.insight.94278] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2017] [Accepted: 06/27/2017] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Dysregulated lipid and glucose metabolism in clear cell renal cell carcinoma (ccRCC) has been implicated in disease progression, and whole tumor tissue-based assessment of these changes is challenged by the tumor heterogeneity. We studied a noninvasive quantitative MRI method that predicts metabolic alterations in the whole tumor. METHODS We applied Dixon-based MRI for in vivo quantification of lipid accumulation (fat fraction [FF]) in targeted regions of interest of 45 primary ccRCCs and correlated these MRI measures to mass spectrometry-based lipidomics and metabolomics of anatomically colocalized tissue samples isolated from the same tumor after surgery. RESULTS In vivo tumor FF showed statistically significant (P < 0.0001) positive correlation with histologic fat content (Spearman correlation coefficient, ρ = 0.79), spectrometric triglycerides (ρ = 0.56) and cholesterol (ρ = 0.47); it showed negative correlation with free fatty acids (ρ = -0.44) and phospholipids (ρ = -0.65). We observed both inter- and intratumoral heterogeneity in lipid accumulation within the same tumor grade, whereas most aggressive tumors (International Society of Urological Pathology [ISUP] grade 4) exhibited reduced lipid accumulation. Cellular metabolites in tumors were altered compared with adjacent renal parenchyma. CONCLUSION Our results support the use of noninvasive quantitative Dixon-based MRI as a biomarker of reprogrammed lipid metabolism in ccRCC, which may serve as a predictor of tumor aggressiveness before surgical intervention. FUNDING NIH R01CA154475 (YZ, MF, PK, IP), NIH P50CA196516 (IP, JB, RJD, JAC, PK), Welch Foundation I-1832 (JY), and NIH P01HL020948 (JGM).
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Affiliation(s)
| | | | - Ling Cai
- Children's Medical Center Research Institute.,Quantitative Biomedical Research Center
| | - Zeping Hu
- Children's Medical Center Research Institute
| | - Payal Kapur
- Pathology.,Urology.,Kidney Cancer Program - Simmons Comprehensive Cancer Center, and
| | | | - Andrea Pavía-Jiménez
- Kidney Cancer Program - Simmons Comprehensive Cancer Center, and.,Internal Medicine, University of Texas (UT) Southwestern Medical Center, Dallas, Texas, USA
| | | | | | | | - Ivan E Dimitrov
- Advanced Imaging Research Center.,Philips Medical Systems, Cleveland, Ohio, USA
| | | | - Jin Ye
- Molecular Genetics, UT Southwestern Medical Center, Dallas, Texas, USA
| | - Matthew A Mitsche
- Molecular Genetics, UT Southwestern Medical Center, Dallas, Texas, USA
| | - Hyeonwoo Kim
- Molecular Genetics, UT Southwestern Medical Center, Dallas, Texas, USA
| | | | | | | | | | | | | | | | - James Brugarolas
- Kidney Cancer Program - Simmons Comprehensive Cancer Center, and.,Internal Medicine, University of Texas (UT) Southwestern Medical Center, Dallas, Texas, USA
| | | | - Ivan Pedrosa
- Radiology.,Advanced Imaging Research Center.,Kidney Cancer Program - Simmons Comprehensive Cancer Center, and
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Xi Y, Yuan Q, Zhang Y, Madhuranthakam AJ, Fulkerson M, Margulis V, Brugarolas J, Kapur P, Cadeddu JA, Pedrosa I. Statistical clustering of parametric maps from dynamic contrast enhanced MRI and an associated decision tree model for non-invasive tumour grading of T1b solid clear cell renal cell carcinoma. Eur Radiol 2017; 28:124-132. [PMID: 28681074 DOI: 10.1007/s00330-017-4925-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2017] [Revised: 04/27/2017] [Accepted: 06/05/2017] [Indexed: 11/29/2022]
Abstract
OBJECTIVES To apply a statistical clustering algorithm to combine information from dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) into a single tumour map to distinguish high-grade from low-grade T1b clear cell renal cell carcinoma (ccRCC). METHODS This prospective, Institutional Review Board -approved, Health Insurance Portability and Accountability Act -compliant study included 18 patients with solid T1b ccRCC who underwent pre-surgical DCE MRI. After statistical clustering of the parametric maps of the transfer constant between the intravascular and extravascular space (K trans ), rate constant (K ep ) and initial area under the concentration curve (iAUC) with a fuzzy c-means (FCM) algorithm, each tumour was segmented into three regions (low/medium/high active areas). Percentages of each region and tumour size were compared to tumour grade at histopathology. A decision-tree model was constructed to select the best parameter(s) to predict high-grade ccRCC. RESULTS Seven high-grade and 11 low-grade T1b ccRCCs were included. High-grade histology was associated with higher percent high active areas (p = 0.0154) and this was the only feature selected by the decision tree model, which had a diagnostic performance of 78% accuracy, 86% sensitivity, 73% specificity, 67% positive predictive value and 89% negative predictive value. CONCLUSIONS The FCM integrates multiple DCE-derived parameter maps and identifies tumour regions with unique pharmacokinetic characteristics. Using this approach, a decision tree model using criteria beyond size to predict tumour grade in T1b ccRCCs is proposed. KEY POINTS • Tumour size did not correlate with tumour grade in T1b ccRCC. • Tumour heterogeneity can be analysed using statistical clustering via DCE-MRI parameters. • High-grade ccRCC has a larger percentage of high active area than low-grade ccRCCs. • A decision-tree model offers a simple way to differentiate high/low-grade ccRCCs.
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Affiliation(s)
- Yin Xi
- Department of Radiology, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, TX, 75235-9085, USA
| | - Qing Yuan
- Department of Radiology, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, TX, 75235-9085, USA
| | - Yue Zhang
- Department of Radiology, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, TX, 75235-9085, USA
| | - Ananth J Madhuranthakam
- Department of Radiology, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, TX, 75235-9085, USA.,Advanced Imaging Research Center, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, TX, USA
| | - Michael Fulkerson
- Department of Radiology, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, TX, 75235-9085, USA
| | - Vitaly Margulis
- Department of Urology, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, TX, USA.,Kidney Cancer Program, Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, TX, USA
| | - James Brugarolas
- Kidney Cancer Program, Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, TX, USA.,Department of Internal Medicine, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, TX, USA
| | - Payal Kapur
- Department of Urology, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, TX, USA.,Kidney Cancer Program, Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, TX, USA.,Department of Pathology, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, Texas, USA
| | - Jeffrey A Cadeddu
- Department of Urology, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, TX, USA.,Kidney Cancer Program, Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, TX, USA
| | - Ivan Pedrosa
- Department of Radiology, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, TX, 75235-9085, USA. .,Advanced Imaging Research Center, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, TX, USA. .,Kidney Cancer Program, Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, TX, USA.
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Clear Cell Papillary Renal Cell Carcinoma: New Clinical and Imaging Characteristics. Urology 2017; 103:136-141. [DOI: 10.1016/j.urology.2016.12.002] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2016] [Revised: 11/24/2016] [Accepted: 12/01/2016] [Indexed: 12/16/2022]
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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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Parada Villavicencio C, Mc Carthy RJ, Miller FH. Can diffusion-weighted magnetic resonance imaging of clear cell renal carcinoma predict low from high nuclear grade tumors. Abdom Radiol (NY) 2017; 42:1241-1249. [PMID: 27904923 DOI: 10.1007/s00261-016-0981-7] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
OBJECTIVE To assess the diagnostic performance of the apparent diffusion coefficient (ADC) in predicting the Fuhrman nuclear grading of clear cell renal cell carcinomas (ccRCC). MATERIALS AND METHODS A total of 129 patients who underwent partial and radical nephrectomies with pathology-proven ccRCC were retrospectively evaluated. Histopathological characteristics and nuclear grades were analyzed. In addition, conventional magnetic resonance imaging (MRI) features were assessed in consensus by two radiologists to discriminate nuclear grading. ADC values were obtained from a region of interest (ROI) measurement in the ADC maps calculated from diffusion-weighted imaging (DWI) using b values of 50, 500, and 800 s/mm2. The threshold values for predicting and differentiating low-grade cancers (Fuhrman I-II) from high grade (Fuhrman III-IV) was obtained using binary logistic regression. The ADC cut-off value for differentiating low- and high-grade tumors was determined using classification analysis. RESULTS Significant associations (P < 0.001) were found between nuclear grading, conventional MR features, and DWI. Hemorrhage, necrosis, perirenal fat invasion, enhancement homogeneity, and cystic component were identified as independent predictors of tumor grade. High-grade ccRCC had significantly lower mean ADC values compared to low-grade tumors. An ADC cut-off value of 1.6 × 10-3 mm2/s had an optimal predictive percentage of 65.5% for low-grade tumors above this threshold and 81% for high-grade ccRCC below this threshold. Overall predictive accuracy was 70.5%. CONCLUSION The addition of ADC values to a model based on MRI conventional features demonstrates increased sensitivity and high specificity improving the distinguishing accuracy between both high-grade and low-grade ccRCC.
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Affiliation(s)
- Carolina Parada Villavicencio
- Department of Radiology, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, 676 North Saint Clair St. Suite 800, Chicago, IL, USA
| | - Robert J Mc Carthy
- Department of Anesthesiology, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, 676 North Saint Clair St. Suite 1050, Chicago, IL, USA
| | - Frank H Miller
- Department of Radiology, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, 676 North Saint Clair St. Suite 800, Chicago, IL, USA.
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Qualitative and Quantitative Imaging Evaluation of Renal Cell Carcinoma Subtypes with Grating-based X-ray Phase-contrast CT. Sci Rep 2017; 7:45400. [PMID: 28361951 PMCID: PMC5374440 DOI: 10.1038/srep45400] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2016] [Accepted: 02/21/2017] [Indexed: 11/13/2022] Open
Abstract
Current clinical imaging methods face limitations in the detection and correct characterization of different subtypes of renal cell carcinoma (RCC), while these are important for therapy and prognosis. The present study evaluates the potential of grating-based X-ray phase-contrast computed tomography (gbPC-CT) for visualization and characterization of human RCC subtypes. The imaging results for 23 ex vivo formalin-fixed human kidney specimens obtained with phase-contrast CT were compared to the results of the absorption-based CT (gbCT), clinical CT and a 3T MRI and validated using histology. Regions of interest were placed on each specimen for quantitative evaluation. Qualitative and quantitative gbPC-CT imaging could significantly discriminate between normal kidney cortex (54 ± 4 HUp) and clear cell (42 ± 10), papillary (43 ± 6) and chromophobe RCCs (39 ± 7), p < 0.05 respectively. The sensitivity for detection of tumor areas was 100%, 50% and 40% for gbPC-CT, gbCT and clinical CT, respectively. RCC architecture like fibrous strands, pseudocapsules, necrosis or hyalinization was depicted clearly in gbPC-CT and was not equally well visualized in gbCT, clinical CT and MRI. The results show that gbPC-CT enables improved discrimination of normal kidney parenchyma and tumorous tissues as well as different soft-tissue components of RCCs without the use of contrast media.
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Oh S, Sung DJ, Yang KS, Sim KC, Han NY, Park BJ, Kim MJ, Cho SB. Correlation of CT imaging features and tumor size with Fuhrman grade of clear cell renal cell carcinoma. Acta Radiol 2017; 58:376-384. [PMID: 27235451 DOI: 10.1177/0284185116649795] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background Identification of clinical features to determine the aggressive potential of tumors is highly warranted to stratify patients for adequate treatment. Computed tomography (CT) imaging features of clear cell renal cell carcinoma (ccRCC) may contribute to personalized risk assessment. Purpose To assess the correlation between CT imaging features and Fuhrman grade of ccRCC, and to identify the predictors of high Fuhrman grade in conjunction with tumor size. Material and Methods CT scans of 169 patients with 173 pathologically proven ccRCCs were retrospectively reviewed in consensus by two radiologists for the presence of intratumoral necrosis and intratumoral cyst and tumor size. Histologic grade was classified as either low (Fuhrman grade I or II) or high (Fuhrman grade III or IV). Statistical significance was evaluated by using univariate, multivariate regression, receiver operating characteristic (ROC) curve, and Spearman correlation analyses. Results On CT, 20 of the 173 tumors had intratumoral cysts, 60 had intratumoral necrosis, and 93 showed entirely solid tumors. The odds of high grade were higher with intratumoral necrosis and entirely solid tumor than with intratumoral cyst ( P < 0.03). Intratumoral necrosis showed a significantly high odds ratio of 25.73 for high Fuhrman grade. The ROC curve showed a threshold tumor size of 36 mm to predict high Fuhrman grade for overall tumors (area under the ROC curve, 0.70). In ccRCCs with intratumoral necrosis or cyst, tumor size did not significantly correlate with Fuhrman grade. Conclusion Intratumoral necrosis on CT was a strong and independent predictor of biologically aggressive ccRCCs, irrespective of tumor size.
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Affiliation(s)
- Saelin Oh
- Department of Radiology, Anam Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Deuk Jae Sung
- Department of Radiology, Anam Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Kyung Sook Yang
- Department of Biostatistics, Korea University College of Medicine, Seoul, Republic of Korea
| | - Ki Choon Sim
- Department of Radiology, Anam Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Na Yeon Han
- Department of Radiology, Anam Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Beom Jin Park
- Department of Radiology, Anam Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Min Ju Kim
- Department of Radiology, Anam Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Sung Bum Cho
- Department of Radiology, Anam Hospital, Korea University College of Medicine, Seoul, Republic of Korea
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47
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Abstract
Detection of solid renal masses has increased, although it has not resulted in significant mortality reduction from renal cell carcinoma. Efforts for improved lesion characterization have been pursued and incorporated in management algorithms, in order to distinguish clinically significant tumors from favorable or benign conditions. Concurrently, imaging methods have produced evidence supporting their role as useful tools not only in lesion detection but also characterization. In addition, newer modalities, such as contrast-enhanced ultrasonography, and advanced applications of MR imaging, are being investigated. This article reviews the current role of different imaging methods in the characterization of solid renal masses.
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Affiliation(s)
- Fernando U Kay
- Department of Radiology, UT Southwestern Medical Center, Harry Hines 5323, 2201 Inwood Road, Dallas, TX 75390, USA
| | - Ivan Pedrosa
- Department of Radiology and Advanced Imaging Research Center, UT Southwestern Medical Center, Harry Hines 5323, 2201 Inwood Road, Dallas, TX 75390, USA.
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48
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Corral de la Calle M, Encinas de la Iglesia J, Martín López M, Fernández Pérez G, Águeda del Bas D. The radiologist's role in the management of papillary renal cell carcinoma. RADIOLOGIA 2017. [DOI: 10.1016/j.rxeng.2017.03.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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49
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Corral de la Calle MÁ, Encinas de la Iglesia J, Martín López MR, Fernández Pérez GC, Águeda Del Bas DS. The radiologist's role in the management of papillary renal cell carcinoma. RADIOLOGIA 2017; 59:100-114. [PMID: 28160948 DOI: 10.1016/j.rx.2016.11.005] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2016] [Revised: 11/05/2016] [Accepted: 11/08/2016] [Indexed: 12/20/2022]
Abstract
Papillary carcinoma is the second most common renal cell carcinoma. It has a better prognosis than the more frequent clear cell carcinoma, although this does not hold true for advanced cases, because no specific treatment exists. It presents as a circumscribed peripheral tumor (small and homogeneously solid or larger and cystic/hemorrhagic) or as an infiltrating lesion that invades the veins, which has a worse prognosis. Due to their low vascular density, papillary renal cell carcinomas enhance less than other renal tumors, and this facilitates their characterization. On computed tomography, they might not enhance conclusively, and in these cases they are impossible to distinguish from hyperattenuating cysts. Contrast-enhanced ultrasonography and magnetic resonance imaging are more sensitive for detecting vascularization. Other characteristics include a specific vascular pattern, hypointensity on T2-weighted images, restricted water diffusion, and increased signal intensity in opposed phase images. We discuss the genetic, histologic, clinical, and radiological aspects of these tumors in which radiologists play a fundamental role in management.
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Affiliation(s)
| | | | - M R Martín López
- Servicio de Anatomía Patológica, Complejo Asistencial de Ávila, Ávila, España
| | - G C Fernández Pérez
- Servicio de Radiodiagnóstico, Hospital Universitario del Río Hortega, Valladolid, España
| | - D S Águeda Del Bas
- Servicio de Radiodiagnóstico, Complejo Asistencial de Ávila, Ávila, España
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50
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Cornelis F, Grenier N. Multiparametric Magnetic Resonance Imaging of Solid Renal Tumors: A Practical Algorithm. Semin Ultrasound CT MR 2017; 38:47-58. [DOI: 10.1053/j.sult.2016.08.009] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
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