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Kang H, Xie W, Wang H, Guo H, Jiang J, Liu Z, Ding X, Li L, Xu W, Zhao J, Bai X, Cui M, Ye H, Wang B, Yang D, Ma X, Liu J, Wang H. Multiparametric MRI-Based Machine Learning Models for the Characterization of Cystic Renal Masses Compared to the Bosniak Classification, Version 2019: A Multicenter Study. Acad Radiol 2024; 31:3223-3234. [PMID: 38242731 DOI: 10.1016/j.acra.2024.01.003] [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: 10/22/2023] [Revised: 12/26/2023] [Accepted: 01/03/2024] [Indexed: 01/21/2024]
Abstract
RATIONALE AND OBJECTIVE Accurate differentiation between benign and malignant cystic renal masses (CRMs) is challenging in clinical practice. This study aimed to develop MRI-based machine learning models for differentiating between benign and malignant CRMs and compare the best-performing model with the Bosniak classification, version 2019 (BC, version 2019). METHODS Between 2009 and 2021, consecutive surgery-proven CRM patients with renal MRI were enrolled in this multicenter study. Models were constructed to differentiate between benign and malignant CRMs using logistic regression (LR), random forest (RF), and support vector machine (SVM) algorithms, respectively. Meanwhile, two radiologists classified CRMs into I-IV categories according to the BC, version 2019 in consensus in the test set. A subgroup analysis was conducted to investigate the performance of the best-performing model in complicated CRMs (II-IV lesions in the test set). The performances of models and BC, version 2019 were evaluated using the area under the receiver operating characteristic curve (AUC). Performance was statistically compared between the best-performing model and the BC, version 2019. RESULTS 278 and 48 patients were assigned to the training and test sets, respectively. In the test set, the AUC and accuracy of the LR model, the RF model, the SVM model, and the BC, version 2019 were 0.884 and 75.0%, 0.907 and 83.3%, 0.814 and 72.9%, and 0.893 and 81.2%, respectively. Neither the AUC nor the accuracy of the RF model that performed best were significantly different from the BC, version 2019 (P = 0.780, P = 0.065). The RF model achieved an AUC and accuracy of 0.880 and 81.0% in complicated CRMs. CONCLUSIONS The MRI-based RF model can accurately differentiate between benign and malignant CRMs with comparable performance to the BC, version 2019, and has good performance in complicated CRMs, which may facilitate treatment decision-making and is less affected by interobserver disagreements.
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Affiliation(s)
- Huanhuan Kang
- Department of Radiology, First Medical Center of Chinese PLA General Hospital, No.28 Fuxing Road, Haidian District, Beijing 100853, China
| | - Wanfang Xie
- School of Engineering Medicine, Beihang University, Beijing 100191, China; Key Laboratory of Big Data-Based Precision Medicine (Beihang University), Ministry of Industry and Information Technology of China, Beijing 100191, China
| | - He Wang
- Radiology Department, Peking University First Hospital, Beijing 100034, China
| | - Huiping Guo
- Department of Radiology, First Medical Center of Chinese PLA General Hospital, No.28 Fuxing Road, Haidian District, Beijing 100853, China
| | - Jiahui Jiang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
| | - Zhe Liu
- Radiology Department, Peking University First Hospital, Beijing 100034, China
| | - Xiaohui Ding
- Department of Pathology, First Medical Center, Chinese PLA General Hospital, Beijing 100853, China
| | - Lin Li
- Hospital Management Institute, Department of Innovative Medical Research, Chinese PLA General Hospital, Outpatient Building, Beijing 100853, China
| | - Wei Xu
- Department of Radiology, First Medical Center of Chinese PLA General Hospital, No.28 Fuxing Road, Haidian District, Beijing 100853, China
| | - Jian Zhao
- Department of Radiology, First Medical Center of Chinese PLA General Hospital, No.28 Fuxing Road, Haidian District, Beijing 100853, China
| | - Xu Bai
- Department of Radiology, First Medical Center of Chinese PLA General Hospital, No.28 Fuxing Road, Haidian District, Beijing 100853, China
| | - Mengqiu Cui
- Department of Radiology, First Medical Center of Chinese PLA General Hospital, No.28 Fuxing Road, Haidian District, Beijing 100853, China
| | - Huiyi Ye
- Department of Radiology, First Medical Center of Chinese PLA General Hospital, No.28 Fuxing Road, Haidian District, Beijing 100853, China
| | - Baojun Wang
- Department of Urology, Third Medical Center of Chinese PLA General Hospital, Beijing 100039, China
| | - Dawei Yang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
| | - Xin Ma
- Department of Urology, Third Medical Center of Chinese PLA General Hospital, Beijing 100039, China
| | - Jiangang Liu
- School of Engineering Medicine, Beihang University, Beijing 100191, China; Key Laboratory of Big Data-Based Precision Medicine (Beihang University), Ministry of Industry and Information Technology of China, Beijing 100191, China
| | - Haiyi Wang
- Department of Radiology, First Medical Center of Chinese PLA General Hospital, No.28 Fuxing Road, Haidian District, Beijing 100853, China.
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Brandi N, Mosconi C, Giampalma E, Renzulli M. Bosniak Classification of Cystic Renal Masses: Looking Back, Looking Forward. Acad Radiol 2024; 31:3237-3247. [PMID: 38199901 DOI: 10.1016/j.acra.2023.12.019] [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: 10/31/2023] [Revised: 11/22/2023] [Accepted: 12/12/2023] [Indexed: 01/12/2024]
Abstract
RATIONALE AND OBJECTIVES According to the 2019 update of the Bosniak classification, the main imaging features that need to be evaluated to achieve a correct characterization of renal cystic masses include the thickness of walls and septa, the number of septa, the appearance of walls and septa, the attenuation/intensity on non-contrast CT/MRI and the presence of unequivocally perceived or measurable enhancement of walls and septa. Despite the improvement deriving from a quantitative evaluation of imaging features, certain limitations seem to persist and some possible scenarios that can be encountered in clinical practice are still missing. MATERIALS AND METHODS A deep analysis of the 2019 update of the Bosniak classification was performed. RESULTS The most notable potential flaws concern: (1) the quantitative measurement of the walls and septa; (2) the fact that walls and septa > 2 mm are always referred to as "enhancing", not considering the alternative scenario; (3) the description of some class II masses partially overlaps with each other and with the definition of class I masses and (4) the morphological variations of cystic masses over time is not considered. CONCLUSION The present paper analyzes in detail the limitations of the 2019 Bosniak classification to improve this important tool and facilitate its use in daily radiological practice.
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Affiliation(s)
- Nicolò Brandi
- Department of Radiology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Via Albertoni 15, Bologna, Italy (N.B., C.M., M.R.).
| | - Cristina Mosconi
- Department of Radiology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Via Albertoni 15, Bologna, Italy (N.B., C.M., M.R.); Department of Radiology, Alma Mater Studiorum University of Bologna, Bologna, Italy (C.M.)
| | - Emanuela Giampalma
- Radiology Unit, Morgagni-Pierantoni Hospital, AUSL Romagna, Forlì, Italy (E.G.)
| | - Matteo Renzulli
- Department of Radiology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Via Albertoni 15, Bologna, Italy (N.B., C.M., M.R.)
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Prata F, Iannuzzi A, Tedesco F, Ragusa A, Civitella A, Pira M, Fantozzi M, Sica L, Scarpa RM, Papalia R. Surgical Outcomes of Hugo™ RAS Robot-Assisted Partial Nephrectomy for Cystic Renal Masses: Technique and Initial Experience. J Clin Med 2024; 13:3595. [PMID: 38930124 PMCID: PMC11204942 DOI: 10.3390/jcm13123595] [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: 05/25/2024] [Revised: 06/17/2024] [Accepted: 06/18/2024] [Indexed: 06/28/2024] Open
Abstract
Background: The Hugo™ Robot-Assisted Surgery (RAS) system is a new cutting-edge robotic platform designed for clinical applications. Nevertheless, its application for cystic renal tumors has not yet been thoroughly investigated. In this context, we present an initial series of Robot-Assisted Partial Nephrectomy (RAPN) procedures carried out using the Hugo™ RAS system for cystic renal masses. Methods: Between October 2022 and January 2024, twenty-seven RAPN procedures for renal tumors were performed at Fondazione Policlinico Universitario Campus Bio-Medico. Our prospective board-approved dataset was queried for "cystic features" (n = 12). Perioperative data were collected. The eGFR was calculated according to the CKD-EPI formula. Post-operative complications were reported according to the Clavien-Dindo classification. Computed tomography (CT) scans for follow-up were performed according to the EAU guidelines. Trifecta was defined as the coexistence of negative surgical margin status, no Clavien-Dindo grade ≥ 3 complications, and eGFR decline ≤ 30%. Results: All the patients successfully underwent RAPN without the need for conversion or additional port placement. The median docking and console time were 5.5 (IQR, 4-6) and 79.5 min (IQR, 58-91 min), respectively. No intraoperative complications occurred, as well as clashes between instruments or with the bedside assistant. Two minor postoperative complications were recorded (Clavien-Dindo II). At discharge, serum creatinine and eGFR were comparable to preoperative values. Only one patient (8.4%) displayed positive surgical margins. The rate of trifecta achievement was 91.7%. Conclusions: RAPN for cystic renal masses using the novel Hugo™ RAS system can be safely and effectively performed. This robotic system provided satisfactory peri-operative outcomes, preserving renal function and displaying low postoperative complications and a high trifecta rate achievement.
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Affiliation(s)
| | - Andrea Iannuzzi
- Department of Urology, Fondazione Policlinico Universitario Campus Bio-Medico, 00128 Rome, Italy; (F.P.); (F.T.); (A.R.); (A.C.); (M.P.); (M.F.); (L.S.); (R.M.S.); (R.P.)
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Járay Á, Farkas PI, Semjén D, Botz B. The Predictive Power of Bosniak 3 and 4 Cystic Renal Lesion Categorization Using Contrast-Enhanced Ultrasound. JOURNAL OF ULTRASOUND IN MEDICINE : OFFICIAL JOURNAL OF THE AMERICAN INSTITUTE OF ULTRASOUND IN MEDICINE 2024; 43:933-949. [PMID: 38284141 DOI: 10.1002/jum.16424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/12/2023] [Revised: 01/13/2024] [Accepted: 01/15/2024] [Indexed: 01/30/2024]
Abstract
OBJECTIVES Contrast-enhanced ultrasound (CEUS) is increasingly utilized for the noninvasive assessment of renal cystic lesions, using the Bosniak grading system. Bosniak 3-4 lesions require surgical referral, which allows correlation with the histopathological outcome. METHODS In this single-center, retrospective study we evaluated renal CEUS exams conducted with SonoVue® with a diagnosis of a Bosniak 3 or 4 lesion between 2019 and 2022. A total of 49 patients and 50 lesions met the inclusion criteria, 31 lesions had available histopathological results. Patient demographics, cyst morphology, and dominant imaging features were registered. The histopathological diagnosis was considered a reference standard. RESULTS Positive predictive power (PPV) for neoplastic lesions was comparable in the Bosniak 3 and 4 categories (75 vs 93.3%, P = .33), while PPV for histopathologically malignant lesion was considerably higher in the latter group (25 vs 93.33%, P = .0002). None of the lesions which had vividly enhancing thin septa as their dominant CEUS feature were malignant. Oncocytoma, multilocular cystic renal neoplasm of low malignant potential, and cystic nephroma were the major benign entities among Bosniak 3 lesions. Localized cystic kidney disease and hemorrhagic cysts were found to be the primary mimickers leading to false positive imaging findings. CONCLUSIONS CEUS has a high predictive power for malignancy in the Bosniak 4 category, which is not maintained in the Bosniak 3 group due to the large proportion of benign lesions. Adherence to rigorous rule-in criteria and active surveillance strategies need to be considered for equivocal CEUS Bosniak 3 lesions.
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Affiliation(s)
- Ákos Járay
- Department of Medical Imaging, University of Pécs, Medical School, Pécs, Hungary
| | - Péter István Farkas
- Department of Medical Imaging, University of Pécs, Medical School, Pécs, Hungary
| | - Dávid Semjén
- Department of Pathology, University of Pécs, Medical School, Pécs, Hungary
| | - Bálint Botz
- Department of Medical Imaging, University of Pécs, Medical School, Pécs, Hungary
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Lucocq J, Morgan L, Rathod K, Szewczyk-Bieda M, Nabi G. Validation of the updated Bosniak classification (2019) in pathologically confirmed CT-categorised cysts. Scott Med J 2024; 69:18-23. [PMID: 38111318 DOI: 10.1177/00369330231221235] [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] [Indexed: 12/20/2023]
Abstract
INTRODUCTION The updated Bosniak classification in 2019 (v2019) addresses vague imaging terms and revises the criteria with the intent to categorise a higher proportion of cysts in lower-risk groups and reduce benign cyst resections. The aim of the present study was to compare the diagnostic accuracy and inter-observer agreement rate of the original (v2005) and updated classifications (v2019). METHOD Resected/biopsied cysts were categorised according to Bosniak classifications (v2005 and v2019) and the diagnostic accuracy was assessed with reference to histopathological analysis. The inter-observer agreement of v2005 and v2019 was determined. RESULTS The malignancy rate of the cohort was 83.6% (51/61). Using v2019, a higher proportion of malignant cysts were categorised as Bosniak ≥ III (88.2% vs 84.3%) and a significantly higher percentage were categorised as Bosniak IV (68.9% vs 47.1%; p = 0.049) in comparison to v2005. v2019 would have resulted in less benign cyst resections (13.5% vs 15.7%). Calcified versus non-calcified cysts had lower rates of malignancy (57.1% vs 91.5%; RR,0.62; p = 0.002). The inter-observer agreement of v2005 was higher than that of v2019 (kappa, 0.70 vs kappa, 0.43). DISCUSSION The updated classification improves the categorisation of malignant cysts and reduces benign cyst resection. The low inter-observer agreement remains a challenge to the updated classification system.
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Affiliation(s)
- James Lucocq
- Department of General Surgery, Victoria Hospital Kirkcaldy, Kirkcaldy, UK
| | - Leo Morgan
- Department of General Surgery, Victoria Hospital Kirkcaldy, Kirkcaldy, UK
| | - Ketan Rathod
- Department of Radiology, Ninewells Hospital, Dundee, UK
| | | | - Ghulam Nabi
- Department of Urology, Ninewells Hospital, Division of Imaging Sciences and Technology, School of Medicine, University of Dundee, Dundee, UK
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Lan L, Yang Y, Xu ZQ, Jin XC, Huang KT, Chen YX, Yang CX, Zhou M. Clinical Evaluation of Cystic Renal Masses With Bosniak Classification by Contrast-Enhanced Ultrasound and Contrast-Enhanced Computer Tomography. JOURNAL OF ULTRASOUND IN MEDICINE : OFFICIAL JOURNAL OF THE AMERICAN INSTITUTE OF ULTRASOUND IN MEDICINE 2023; 42:2845-2858. [PMID: 37732901 DOI: 10.1002/jum.16324] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/10/2022] [Revised: 08/10/2023] [Accepted: 08/11/2023] [Indexed: 09/22/2023]
Abstract
OBJECTIVES The study aims to compare retrospectively three clinically applied methods for the diagnostic performance of cystic renal masses (CRMs) by contrast-enhanced ultrasound (CEUS) and contrast-enhanced computer tomography (CECT) with Bosniak classification system. METHODS A total of 52 cases of Bosniak II-IV CRMs in 49 consecutive patients were diagnosed from January 2013 to July 2022 and their data were analyzed. All patients had been subjected to CEUS and CECT simultaneously. Pathological diagnoses and masses stability were used as standard references to determine whether lesions were malignant or benign. Then 49 CRMs only with pathologic results were classified into group 1 and 2. RESULTS A total of 52 CRMs in 49 enrolled patients were classified into 8 category II, 16 category IIF, 15 category III, and 13 category IV by CEUS (EFSUMB 2020), 10 category II, 13 category IIF, 16 category III, and 13 category IV by CEUS (V2019), while 15 category II, 9 category IIF, 13 category III, and 15 category IV by CECT (V2019). Pathological results and masses stability longer than 5 years follow-up performed substantially for CEUS (EFSUMB 2020), CEUS (V2019), and CECT (V2019) (kappa values were 0.696, 0.735, and 0.696, respectively). Among 49 pathologic approving CRMs, wall/septation thickness ≥4 mm, wall/septation thickness, presence of enhancing nodule and the diameter were found to be statistically significant for malignancy. Twenty-two malignant masses were correctly diagnosed by CEUS (V2019), while 21 malignant masses were both correctly diagnosed by CEUS (EFSUMB 2020) and CECT (V2019), and 1 mass was misdiagnosed. CONCLUSIONS Bosniak classification of EFSUMB 2020 version might be as accurate as version 2019 CEUS and version 2019 CECT in diagnosing CRMs, and CEUS is found to have an excellent safety profile in dealing with clinical works.
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Affiliation(s)
- Li Lan
- Department of Ultrasound, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Yu Yang
- Department of Urology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Zi-Qiang Xu
- Department of Urology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Xuan-Chen Jin
- School of the First Clinical Medical Sciences (School of Information and Engineering), Wenzhou Medical University, Wenzhou, China
| | - Ka-Te Huang
- Department of Pathology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Yu-Xuan Chen
- School of the First Clinical Medical Sciences (School of Information and Engineering), Wenzhou Medical University, Wenzhou, China
| | - Chen-Xing Yang
- Department of Ultrasound, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Man Zhou
- Department of Ultrasound, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
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Das CJ, Agarwal K, Sharma S, Seth A. Role of Contrast-Enhanced Ultrasound in Evaluation of Cystic Renal Mass. JOURNAL OF ULTRASOUND IN MEDICINE : OFFICIAL JOURNAL OF THE AMERICAN INSTITUTE OF ULTRASOUND IN MEDICINE 2023; 42:2873-2881. [PMID: 37676901 DOI: 10.1002/jum.16328] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 08/20/2023] [Accepted: 08/21/2023] [Indexed: 09/09/2023]
Abstract
OBJECTIVES Contrast-enhanced ultrasound (CEUS) allows excellent delineation of perfusion in septa and nodules without exposure to ionizing radiation or nephrotoxic contrast media. The aim of our study was to evaluate the role of CEUS for the assessment of cystic renal masses and compare its diagnostic performance with that of CECT. METHODS Exactly 40 patients diagnosed to have cystic renal masses on CECT scan were prospectively evaluated with CEUS and were assigned a Bosniak class. Based on results of final histopathology and clinical follow-up, internal validity of both CEUS and CECT was evaluated, including agreement between these two modalities. RESULTS Out of the 40 patients (mean size 3.1 ± 2.5 cm), 23 patients had benign lesions and 17 patients had malignant lesions. For CEUS, the sensitivity and negative predictive value was 100%, the specificity and positive predictive value was 73.9%. For CECT, the sensitivity and negative predictive value were 88.2 and 83.3%, respectively, whereas the specificity and positive predictive value was 87 and 90.9%, respectively. Both imaging modalities had similar accuracy with fair to good agreement with the final diagnosis (Κ = 0.71 and 0.75 for CEUS and CECT, respectively). Concordance between CEUS and CECT was seen in 29 patients (72.5%) with fair agreement between the two modalities (K = 0.66). CONCLUSION CEUS has comparable accuracy with CECT and could be used as screening modality to rule out the presence of complex cystic renal masses without exposure of nephrotoxic contrast media and ionizing radiation.
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Affiliation(s)
- Chandan J Das
- Department of Radiodiagnosis and Interventional Radiology, All India Institute of Medical Sciences (AIIMS), New Delhi, India
| | - Keshav Agarwal
- Department of Urology, All India Institute of Medical Sciences (AIIMS), New Delhi, India
| | - Sanjay Sharma
- Department of Radiodiagnosis, RP Centre, All India Institute of Medical Sciences (AIIMS), New Delhi, India
| | - Amlesh Seth
- Department of Radiodiagnosis and Interventional Radiology, All India Institute of Medical Sciences (AIIMS), New Delhi, India
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Möller K, Jenssen C, Correas JM, Safai Zadeh E, Bertolotto M, Ignee A, Dong Y, Cantisani V, Dietrich CF. CEUS Bosniak Classification-Time for Differentiation and Change in Renal Cyst Surveillance. Cancers (Basel) 2023; 15:4709. [PMID: 37835403 PMCID: PMC10571952 DOI: 10.3390/cancers15194709] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 09/12/2023] [Accepted: 09/20/2023] [Indexed: 10/15/2023] Open
Abstract
It is time for a change. CEUS is an established method that should be much more actively included in renal cyst monitoring strategies. This review compares the accuracies, strengths, and weaknesses of CEUS, CECT, and MRI in the classification of renal cysts. In order to avoid overstaging by CEUS, a further differentiation of classes IIF, III, and IV is required. A further development in the refinement of the CEUS-Bosniak classification aims to integrate CEUS more closely into the monitoring of renal cysts and to develop new and complex monitoring algorithms.
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Affiliation(s)
- Kathleen Möller
- Medical Department I/Gastroenterology, Sana Hospital Lichtenberg, 10365 Berlin, Germany
| | - Christian Jenssen
- Department of Internal Medicine, Krankenhaus Märkisch-Oderland, 15344 Strausberg, Germany
- Brandenburg Institute of Clinical Medicine, Medical University Brandenburg, 16816 Neuruppin, Germany
| | - Jean Michel Correas
- Biomedical Imaging Laboratory, UMR 7371-U114, University of Paris, 75006 Paris, France
| | - Ehsan Safai Zadeh
- Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria
| | - Michele Bertolotto
- Department of Radiology, Ospedale di Cattinara, University of Trieste, 34149 Trieste, Italy
| | - André Ignee
- Department of Medical Gastroenterology, Julius-Spital, 97070 Würzburg, Germany
| | - Yi Dong
- Department of Ultrasound, Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai 200092, China
| | - Vito Cantisani
- Department of Radiology, Oncology, and Anatomy Pathology, “Sapienza” University of Rome, 00185 Rome, Italy
| | - Christoph F. Dietrich
- Department Allgemeine Innere Medizin, Hirslanden Klinik Beau-Site, 3013 Bern, Switzerland
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Alkhamis K, Alsasi O, Alzahrani M. The Modified Bosniak Classification for Intermediate and High-Risk Renal Cysts. Cureus 2023; 15:e37331. [PMID: 37181991 PMCID: PMC10168524 DOI: 10.7759/cureus.37331] [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] [Accepted: 04/05/2023] [Indexed: 05/16/2023] Open
Abstract
Background Renal cysts are uncommon among the pediatric population, and their transformation into malignant lesions is also uncommon. Early detection can prevent further complications and protect renal function. Bosniak classification is a computed tomography-based classification for renal cysts developed for adults. Children are more susceptible to CT radiation. Therefore, a modified Bosniak classification for children based on the ultrasound (US) can be used if it shows reliability and accuracy. Aim To apply the modified Bosniak classification system among children with renal cysts. Methods This was a retrospective study that was conducted on pediatric patients who underwent surgery for intermediate and high-risk complex renal cysts in Prince Sultan Military Medical City, Riyadh, Saudi Arabia using radiological information from 2009 to 2022. The collected data included demographics, medical history, radiological findings, and characteristics of renal cysts. SPSS Statistics v. 22 (IBM Corp., Armonk, NY) was used to analyze the data. Results There were 40 children included in the study based on the US-modified Bosniak classification. Around 26.3% of patients had class I and 39.5% had class II renal cysts. Histopathology showed that 10% had Wilms tumor, and 15% had benign lesions. There were significant correlations between pathology findings and US findings (p=0.004), and CT findings (p=0.016). Conclusion The modified Bosniak classification based on the US is sensitive, specific, and sufficiently accurate in the classification of renal cysts among children. Also, the size of the renal cysts can be a diagnostic marker of differentiation of benign and malignant cysts with high sensitivity and specificity.
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Affiliation(s)
- Khalid Alkhamis
- Radiodiagnostics and Medical Imaging Department, Prince Sultan Military Medical City, Riyadh, SAU
| | - Omai Alsasi
- Radiodiagnostics and Medical Imaging Department, Prince Sultan Military Medical City, Riyadh, SAU
| | - Mohammed Alzahrani
- Radiodiagnostics and Medical Imaging Department, Prince Sultan Military Medical City, Riyadh, SAU
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Gobara A, Yoshizako T, Yoshida R, Katsube T, Ishikura Y, Kamimura T, Kaji Y. Radiological Features of T1a Renal Cell Carcinoma on Axial Unenhanced Computed Tomography. Cureus 2023; 15:e36881. [PMID: 37123667 PMCID: PMC10147534 DOI: 10.7759/cureus.36881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/29/2023] [Indexed: 03/31/2023] Open
Abstract
CT has become a commonly used diagnostic procedure in clinical practice, particularly in emergency healthcare delivery. Accordingly, the increase in CT usage has increased the likelihood of incidental detections (ID) of renal cell carcinomas (RCCs). This article discusses key points and limitations associated with the diagnosis and characterization of T1a RCC (≤4 cm in diameter) and shows how to improvise on the differentiation of T1a RCC with unenhanced CT (UE-CT). We retrospectively reviewed UE-CT findings of cases associated with the histopathologic diagnosis of T1a RCC and examined the discrimination capacity and radiological characteristics with regard to small RCCs (SRCCs). Detection and characterization of T1a RCC based on UE-CT are not easy in many cases due to limitations in CT findings, but there are notable radiological features to facilitate detection and differentiation. The growth pattern is important for the detection of SRCCs. Internal characteristic features (average attenuation, heterogeneity) are useful for the characterization of the RCC. In addition, CT image visualization techniques may help improve the detectability of RCCs on UE-CT. Radiological features are important in detecting SRCCs and facilitating further examination. In this study, we discuss some cases of T1a RCCs and evaluate the radiological characteristics of the tumors seen on UE-CT.
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Anush A, Rohini G, Nicola S, WalaaEldin EM, Eranga U. Deep-learning-based ensemble method for fully automated detection of renal masses on magnetic resonance images. J Med Imaging (Bellingham) 2023; 10:024501. [PMID: 36950139 PMCID: PMC10026851 DOI: 10.1117/1.jmi.10.2.024501] [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: 05/18/2022] [Accepted: 02/22/2023] [Indexed: 03/24/2023] Open
Abstract
Purpose Accurate detection of small renal masses (SRM) is a fundamental step for automated classification of benign and malignant or indolent and aggressive renal tumors. Magnetic resonance image (MRI) may outperform computed tomography (CT) for SRM subtype differentiation due to improved tissue characterization, but is less explored compared to CT. The objective of this study is to autonomously detect SRM on contrast-enhanced magnetic resonance images (CE-MRI). Approach In this paper, we described a novel, fully automated methodology for accurate detection and localization of SRM on CE-MRI. We first determine the kidney boundaries using a U-Net convolutional neural network. We then search for SRM within the localized kidney regions using a mixture-of-experts ensemble model based on the U-Net architecture. Our dataset contained CE-MRI scans of 118 patients with different solid kidney tumor subtypes including renal cell carcinomas, oncocytomas, and fat-poor renal angiomyolipoma. We evaluated the proposed model on the entire CE-MRI dataset using 5-fold cross validation. Results The developed algorithm reported a Dice similarity coefficient of 91.20 ± 5.41 % (mean ± standard deviation) for kidney segmentation from 118 volumes consisting of 25,025 slices. Our proposed ensemble model for SRM detection yielded a recall and precision of 86.2% and 83.3% on the entire CE-MRI dataset, respectively. Conclusions We described a deep-learning-based method for fully automated SRM detection using CE-MR images, which has not been studied previously. The results are clinically important as SRM localization is a pre-step for fully automated diagnosis of SRM subtypes.
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Affiliation(s)
- Agarwal Anush
- University of Guelph, School of Engineering, Guelph, Ontario, Canada
| | - Gaikar Rohini
- University of Guelph, School of Engineering, Guelph, Ontario, Canada
| | - Schieda Nicola
- University of Ottawa, Department of Radiology, Ottawa, Ontario, Canada
| | | | - Ukwatta Eranga
- University of Guelph, School of Engineering, Guelph, Ontario, Canada
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12
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Nate T, Hatano K, Kato T, Kawashima A, Abe T, Fukuhara S, Uemura M, Kiuchi H, Imamura R, Nonomura N. Mucinous cystadenoma of the renal parenchyma presenting as a Bosniak IIF complex renal cyst. IJU Case Rep 2023; 6:150-153. [PMID: 36874994 PMCID: PMC9978073 DOI: 10.1002/iju5.12576] [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: 11/04/2022] [Accepted: 01/07/2023] [Indexed: 01/20/2023] Open
Abstract
Introduction A primary retroperitoneal mucinous cystadenoma should be surgically resected because of the risk of malignant transformation. However, mucinous cystadenoma of the renal parenchyma is very rare, and preoperative imaging mimics complicated renal cysts. Case presentation A 72-year-old woman presented with a right renal mass on computed tomography that was followed up as a Bosniak IIF complicated renal cyst. One year later, the right renal mass gradually increased in size. Abdominal computed tomography showed an 11 × 10 cm mass in the right kidney. A laparoscopic right nephrectomy was performed because cystic carcinoma of the kidney was suspected. Pathologically, the tumor was diagnosed as mucinous cystadenoma of the renal parenchyma. Eighteen months after resection, the disease has not recurred. Conclusion Here, we experienced a case of a renal mucinous cystadenoma as a slowly enlarging Bosniak IIF complex renal cyst.
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Affiliation(s)
- Takanori Nate
- Department of Urology Osaka University Graduate School of Medicine Suita Japan
| | - Koji Hatano
- Department of Urology Osaka University Graduate School of Medicine Suita Japan
| | - Taigo Kato
- Department of Urology Osaka University Graduate School of Medicine Suita Japan
| | - Atsunari Kawashima
- Department of Urology Osaka University Graduate School of Medicine Suita Japan
| | - Toyofumi Abe
- Department of Urology Osaka University Graduate School of Medicine Suita Japan
| | - Shinichiro Fukuhara
- Department of Urology Osaka University Graduate School of Medicine Suita Japan
| | - Motohide Uemura
- Department of Urology Osaka University Graduate School of Medicine Suita Japan
| | - Hiroshi Kiuchi
- Department of Urology Osaka University Graduate School of Medicine Suita Japan
| | - Ryoichi Imamura
- Department of Urology Osaka University Graduate School of Medicine Suita Japan
| | - Norio Nonomura
- Department of Urology Osaka University Graduate School of Medicine Suita Japan
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13
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Herms E, Weirich G, Maurer T, Wagenpfeil S, Preuss S, Sauter A, Heck M, Gärtner A, Hauner K, Autenrieth M, Kübler HP, Holzapfel K, Schwarz-Boeger U, Heemann U, Slotta-Huspenina J, Stock KF. Ultrasound-based "CEUS-Bosniak"classification for cystic renal lesions: an 8-year clinical experience. World J Urol 2023; 41:679-685. [PMID: 35986781 PMCID: PMC10082702 DOI: 10.1007/s00345-022-04094-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Accepted: 07/07/2022] [Indexed: 11/25/2022] Open
Abstract
PURPOSE Renal cysts comprise benign and malignant entities. Risk assessment profits from CT/MRI imaging using the Bosniak classification. While Bosniak-IIF, -III, and -IV cover complex cyst variants, Bosniak-IIF and -III stand out due to notorious overestimation. Contrast-enhanced ultrasound (CEUS) is promising to overcome this deficit but warrants standardization. This study addresses the benefits of a combined CEUS and CT/MRI evaluation of renal cysts. The study provides a realistic account of kidney tumor boards' intricacies in trying to validate renal cysts. METHODS 247 patients were examined over 8 years. CEUS lesions were graded according to CEUS-Bosniak (IIF, III, IV). 55 lesions were resected, CEUS-Bosniak- and CT/MRI-Bosniak-classification were correlated with histopathological diagnosis. Interobserver agreement between the classifications was evaluated statistically. 105 lesions were followed by ultrasound, and change in CEUS-Bosniak-types and lesion size were documented. RESULTS 146 patients (156 lesions) were included. CEUS classified 67 lesions as CEUS-Bosniak-IIF, 44 as CEUS-Bosniak-III, and 45 as CEUS-Bosniak-IV. Histopathology of 55 resected lesions revealed benign cysts in all CEUS-Bosniak-IIF lesions (2/2), 40% of CEUS-Bosniak-III and 8% of CEUS-Bosniak-IV, whereas malignancy was uncovered in 60% of CEUS-Bosniak-III and 92% of CEUS-Bosniak-IV. Overall, CEUS-Bosniak-types matched CT/MRI-Bosniak types in 58% (fair agreement, κ = 0.28). CEUS-Bosniak resulted in higher stages than CT/MRI-Bosniak (40%). Ultrasound follow-up of 105 lesions detected no relevant differences between CEUS-Bosniak-types concerning cysts size. 99% of lesions showed the same CEUS-Bosniak-type. CONCLUSION The CEUS-Bosniak classification is an essential tool in clinical practice to differentiate and monitor renal cystic lesions and empowers diagnostic work-up and patient care.
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Affiliation(s)
- Elena Herms
- Department of Nephrology, University Hospital MRI-TUM (München Rechts Der Isar), Munich, Germany
| | - Gregor Weirich
- Institute of Pathology, University Hospital MRI-TUM (München Rechts Der Isar), Munich, Germany
| | - Tobias Maurer
- Department of Urology and Martini-Klinik, University Hospital Hamburg-Eppendorf, Hamburg, Germany
| | - Stefan Wagenpfeil
- Institute of Medical Biometry, Epidemiology and Medical Informatics (IMBEI), Saarland University, Campus Homburg, Homburg, Germany
| | - Stephanie Preuss
- Department of Nephrology, University Hospital MRI-TUM (München Rechts Der Isar), Munich, Germany
| | - Andreas Sauter
- Department of Radiology, University Hospital MRI-TUM (München Rechts Der Isar), Munich, Germany
| | - Matthias Heck
- Department of Urology, University Hospital MRI-TUM (München Rechts Der Isar), Munich, Germany
| | - Anita Gärtner
- Department of Anesthesia, Freising University Hospital, Freising, Germany
| | - Katharina Hauner
- Department of Urology, University Hospital MRI-TUM (München Rechts Der Isar), Munich, Germany
| | - Michael Autenrieth
- Department of Urology, University Hospital MRI-TUM (München Rechts Der Isar), Munich, Germany
| | - Hubert P Kübler
- Department of Urology, University Hospital Würzburg, Würzburg, Germany
| | | | - Ulrike Schwarz-Boeger
- Medical Controlling, University Hospital MRI-TUM (München Rechts Der Isar), Munich, Germany
| | - Uwe Heemann
- Department of Nephrology, University Hospital MRI-TUM (München Rechts Der Isar), Munich, Germany
| | - Julia Slotta-Huspenina
- Institute of Pathology, University Hospital MRI-TUM (München Rechts Der Isar), Munich, Germany
| | - Konrad Friedrich Stock
- Department of Nephrology, University Hospital MRI-TUM (München Rechts Der Isar), Munich, Germany.
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14
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Dana J, Gauvin S, Zhang M, Lotero J, Cassim C, Artho G, Bhatnagar SR, Tanguay S, Reinhold C. CT-based Bosniak classification of cystic renal lesions: is version 2019 an improvement on version 2005? Eur Radiol 2023; 33:1297-1306. [PMID: 36048207 DOI: 10.1007/s00330-022-09082-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2022] [Revised: 07/02/2022] [Accepted: 08/04/2022] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To compare the diagnostic performance and inter-reader agreement of the CT-based v2019 versus v2005 Bosniak classification systems for risk stratification of cystic renal lesions (CRL). METHODS This retrospective study included adult patients with CRL identified on CT scan between 2005 and 2018. The reference standard was histopathology or a minimum 4-year imaging follow-up. The studies were reviewed independently by five readers (three senior, two junior), blinded to pathology results and imaging follow-up, who assigned Bosniak categories based on the 2005 and 2019 versions. Diagnostic performance of v2005 and v2019 Bosniak classifications for distinguishing benign from malignant lesions was calculated by dichotomizing CRL into the potential for ablative therapy (III-IV) or conservative management (I-IIF). Inter-reader agreement was calculated using Light's Kappa. RESULTS One hundred thirty-nine patients with 149 CRL (33 malignant) were included. v2005 and v2019 Bosniak classifications achieved similar diagnostic performance with a sensitivity of 91% vs 91% and a specificity of 89% vs 88%, respectively. Inter-reader agreement for overall Bosniak category assignment was substantial for v2005 (κ = 0.78) and v2019 (κ = 0.75) between senior readers but decreased for v2019 when the Bosniak classification was dichotomized to conservative management (I-IIF) or ablative therapy (III-IV) (0.80 vs 0.71, respectively). For v2019, wall thickness was the morphological feature with the poorest inter-reader agreement (κ = 0.43 and 0.18 for senior and junior readers, respectively). CONCLUSION No significant improvement in diagnostic performance and inter-reader agreement was shown between v2005 and v2019. The observed decrease in inter-reader agreement in v2019 when dichotomized according to management strategy may reflect the more stringent morphological criteria. KEY POINTS • Versions 2005 and 2019 Bosniak classifications achieved similar diagnostic performance, but the specificity of higher risk categories (III and IV) was not increased while one malignant lesion was downgraded to v2019 Bosniak category II (i.e., not subjected to further follow-up). • Inter-reader agreement was similar between v2005 and v2019 but moderately decreased for v2019 when the Bosniak classification was dichotomized according to the potential need for ablative therapies (I-II-IIF vs III-IV).
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Affiliation(s)
- Jérémy Dana
- Department of Diagnostic Radiology, McGill University Health Center, 1001 Decarie Boul., H4A 3J1, Montréal, Québec, Canada.,Strasbourg University, Inserm U1110, Institut de Recherche sur les Maladies Virales et Hépatiques, Strasbourg, France.,IHU-Strasbourg (Institut Hospitalo-Universitaire), Institute for Minimally Invasive Hybrid Image-Guided Surgery, Université de Strasbourg, Strasbourg, France
| | - Simon Gauvin
- Department of Diagnostic Radiology, McGill University Health Center, 1001 Decarie Boul., H4A 3J1, Montréal, Québec, Canada.,Montreal Imaging Experts Inc., Montreal, Canada
| | - Michelle Zhang
- Department of Diagnostic Radiology, McGill University Health Center, 1001 Decarie Boul., H4A 3J1, Montréal, Québec, Canada.,Montreal Imaging Experts Inc., Montreal, Canada
| | - Jose Lotero
- Department of Diagnostic Radiology, McGill University Health Center, 1001 Decarie Boul., H4A 3J1, Montréal, Québec, Canada
| | - Christopher Cassim
- Department of Diagnostic Radiology, McGill University Health Center, 1001 Decarie Boul., H4A 3J1, Montréal, Québec, Canada
| | - Giovanni Artho
- Department of Diagnostic Radiology, McGill University Health Center, 1001 Decarie Boul., H4A 3J1, Montréal, Québec, Canada.,Montreal Imaging Experts Inc., Montreal, Canada
| | - Sahir Rai Bhatnagar
- Department of Diagnostic Radiology, McGill University Health Center, 1001 Decarie Boul., H4A 3J1, Montréal, Québec, Canada.,Department of Epidemiology, Biostatistics and Occupational Health, McGill University Health Center, Montréal, Québec, Canada
| | - Simon Tanguay
- Department of Urology, McGill University Health Center, Montréal, Québec, Canada
| | - Caroline Reinhold
- Department of Diagnostic Radiology, McGill University Health Center, 1001 Decarie Boul., H4A 3J1, Montréal, Québec, Canada. .,Montreal Imaging Experts Inc., Montreal, Canada. .,Augmented Intelligence & Precision Health Laboratory of the Research Institute of McGill University Health Centre, Montreal, Canada.
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15
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Almalki YE, Basha MAA, Refaat R, Alduraibi SK, Abdalla AAEHM, Yousef HY, Zaitoun MMA, Elsayed SB, Mahmoud NEM, Alayouty NA, Ali SA, Alnaggar AA, Saber S, El-Maghraby AM, Elsheikh AM, Radwan MHSS, Abdelmegid AGI, Aly SA, Shanab WSA, Obaya AA, Abdelhai SF, Elshorbagy S, Haggag YM, Mokhtar HM, Sabry NM, Altohamy JI, Abouelkheir RT, Omran T, Shalan A, Algazzar YH, Metwally MI. Bosniak classification version 2019: a prospective comparison of CT and MRI. Eur Radiol 2023; 33:1286-1296. [PMID: 35962816 DOI: 10.1007/s00330-022-09044-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 06/13/2022] [Accepted: 07/19/2022] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To assess the diagnostic accuracy and agreement of CT and MRI in terms of the Bosniak classification version 2019 (BCv2019). MATERIALS AND METHODS A prospective multi-institutional study enrolled 63 patients with 67 complicated cystic renal masses (CRMs) discovered during ultrasound examination. All patients underwent CT and MRI scans and histopathology. Three radiologists independently assessed CRMs using BCv2019 and assigned Bosniak class to each CRM using CT and MRI. The final analysis included 60 histopathologically confirmed CRMs (41 were malignant and 19 were benign). RESULTS Discordance between CT and MRI findings was noticed in 50% (30/60) CRMs when data were analyzed in terms of the Bosniak classes. Of these, 16 (53.3%) were malignant. Based on consensus reviewing, there was no difference in the sensitivity, specificity, and accuracy of the BCv2019 with MRI and BCv2019 with CT (87.8%; 95% CI = 73.8-95.9% versus 75.6%; 95% CI = 59.7-87.6%; p = 0.09, 84.2%; 95% CI = 60.4-96.6% versus 78.9%; 95% CI = 54.4-93.9%; p = 0.5, and 86.7%; 95% CI = 64.0-86.6% versus 76.7%; 95% CI = 75.4-94.1%; p = 0.1, respectively). The number and thickness of septa and the presence of enhanced nodules accounted for the majority of variations in Bosniak classes between CT and MRI. The inter-reader agreement (IRA) was substantial for determining the Bosniak class in CT and MRI (k = 0.66; 95% CI = 0.54-0.76, k = 0.62; 95% CI = 0.50-0.73, respectively). The inter-modality agreement of the BCv219 between CT and MRI was moderate (κ = 0.58). CONCLUSION In terms of BCv2019, CT and MRI are comparable in the classification of CRMs with no significant difference in diagnostic accuracy and reliability. KEY POINTS • There is no significant difference in the sensitivity, specificity, and accuracy of the BCv2019 with MRI and BCv2019 with CT. • The number of septa and their thickness and the presence of enhanced nodules accounted for the majority of variations in Bosniak classes between CT and MRI. • The inter-reader agreement was substantial for determining the Bosniak class in CT and MRI and the inter-modality agreement of the BCv219 between CT and MRI was moderate.
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Affiliation(s)
- Yassir Edrees Almalki
- Division of Radiology, Department of Internal Medicine, Medical College, Najran University, Najran, Kingdom of Saudi Arabia
| | | | - Rania Refaat
- Department of Diagnostic Radiology, Intervention and Molecular Imaging, Faculty of Human Medicine, Ain Shams University, Cairo, Egypt
| | - Sharifa Khalid Alduraibi
- Department of Radiology, College of Medicine, Qassim University, Buraidah, Kingdom of Saudi Arabia
| | | | - Hala Y Yousef
- Department of Diagnostic Radiology, Faculty of Human Medicine, Zagazig University, Zagazig, Egypt
| | - Mohamed M A Zaitoun
- Department of Diagnostic Radiology, Faculty of Human Medicine, Zagazig University, Zagazig, Egypt
| | - Saeed Bakry Elsayed
- Department of Diagnostic Radiology, Faculty of Human Medicine, Zagazig University, Zagazig, Egypt
| | - Nader E M Mahmoud
- Department of Diagnostic Radiology, Faculty of Human Medicine, Zagazig University, Zagazig, Egypt
| | - Nader Ali Alayouty
- Department of Diagnostic Radiology, Faculty of Human Medicine, Zagazig University, Zagazig, Egypt
| | - Susan Adil Ali
- Department of Diagnostic Radiology, Intervention and Molecular Imaging, Faculty of Human Medicine, Ain Shams University, Cairo, Egypt
| | - Ahmad Abdullah Alnaggar
- Department of Diagnostic Radiology, Faculty of Human Medicine, Zagazig University, Zagazig, Egypt
| | - Sameh Saber
- Department of Diagnostic Radiology, Faculty of Human Medicine, Zagazig University, Zagazig, Egypt
| | | | - Amgad M Elsheikh
- Department of Diagnostic Radiology, Faculty of Human Medicine, Zagazig University, Zagazig, Egypt
| | | | | | - Sameh Abdelaziz Aly
- Department of Diagnostic Radiology, Faculty of Human Medicine, Benha University, Benha, Egypt
| | - Waleed S Abo Shanab
- Department of Diagnostic Radiology, Faculty of Human Medicine, Port Said University, Port Said, Egypt
| | - Ahmed Ali Obaya
- Department of Clinical Oncology, Faculty of Human Medicine, Zagazig University, Zagazig, Egypt
| | - Shaimaa Farouk Abdelhai
- Department of Clinical Oncology, Faculty of Human Medicine, Zagazig University, Zagazig, Egypt
| | - Shereen Elshorbagy
- Department of Medical Oncology, Faculty of Human Medicine, Zagazig University, Zagazig, Egypt
| | - Yasser M Haggag
- Department of Urology, Faculty of Human Medicine, Al Azhar University, Cairo, Egypt
| | - Hwaida M Mokhtar
- Department of Diagnostic Radiology, Faculty of Human Medicine, Tanta University, Tanta, Egypt
| | - Nesreen M Sabry
- Department of Clinical Oncology, Faculty of Human Medicine, Tanta University, Tanta, Egypt
| | - Jehan Ibrahim Altohamy
- Department of Diagnostic Radiology, National Institute of Urology and Nephrology, Cairo, Egypt
| | - Rasha Taha Abouelkheir
- Department of Diagnostic Radiology, Urology and Nephrology Center, Mansoura University, Mansoura, Egypt
| | - Tawfik Omran
- Department of Diagnostic Radiology, Faculty of Human Medicine, Helwan University, Cairo, Egypt
| | - Ahmed Shalan
- Department of Diagnostic Radiology, Faculty of Human Medicine, Benha University, Benha, Egypt
| | | | - Maha Ibrahim Metwally
- Department of Diagnostic Radiology, Faculty of Human Medicine, Zagazig University, Zagazig, Egypt
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16
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Angelini L, Gioulis E, Civitareale N, Granata A, Zanza C, Longhitano Y, Zago A, Machin P, Canal F, Serao A, Piccoli G, Valerio S. Assessment of Contrast-Enhanced Ultrasound (CEUS) and Computed Tomography (CT) diagnostic accuracy in the evaluation of challenging cystic renal masses. J Ultrasound 2022; 25:905-913. [PMID: 35460506 PMCID: PMC9705654 DOI: 10.1007/s40477-022-00683-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Accepted: 03/28/2022] [Indexed: 10/18/2022] Open
Abstract
PURPOSE To assess the diagnostic accuracy of contrast-enhanced ultrasound (CEUS) and computed tomography (CT) within Bosniak IIF/III categories. METHODS After cystic renal mass diagnosis by contrast-enhanced CT, all patients with Bosniak score ≥ II also underwent CEUS between March 2017 and March 2019. Their exams were retrospectively analyzed. One experienced uro-radiologist performed every CEUS and reviewed the exams according to the EFSUMB 2020 Position Statement, while blinded to clinical data. CT Bosniak scores were retrospectively given blindly by two uro-radiologists (CT 1 and CT 2). We compared CEUS, CT 1 and CT 2 scores to clinical findings and histological tests. Clinical performance characteristics and area under the receiver operating characteristic (ROC) curves (AUCs) were determined separately for CEUS and CT, and then compared. RESULTS 101 cystic masses were analyzed. In Bosniak categories IIF and III, the AUCs were 0.854 for CT 1, 0.779 for CT 2, and 0.746 for CEUS. CONCLUSION Despite some statistical limitations, this study confirms that among cystic renal masses, those classified as Bosniak IIF and III are the most difficult to assess. The diagnostic performances of CEUS and CT are similar within this group. However, in experienced hands, CEUS could be valuable in further evaluation of ambiguous cystic masses, and in more ductile, safer, and cost-effective surveillance of those classified as Bosniak IIF and III. When challenging cystic renal masses occur, CEUS is a useful tool for clinical management and for the follow-up of non-surgical lesions.
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Affiliation(s)
- Lorenzo Angelini
- Department of Surgery, Section of Urology, SS Antonio and Biagio and Cesare Arrigo Hospital, Via Venezia, 16, 15121, Alessandria, Italy.
| | - Eugenio Gioulis
- Department of Radiology, Conegliano Hospital, Conegliano, Italy
| | | | - Antonio Granata
- Nephrology and Dialysis Unit, Emergency Hospital "Cannizzaro", Catania, Italy
| | - Christian Zanza
- Department of Emergency Medicine, Anesthesia and Critical Care, Michele and Pietro Ferrero Hospital, Verduno, Italy
| | - Yaroslava Longhitano
- Department of Anesthesia and Critical Care, SS Antonio and Biagio and Cesare Arrigo Hospital, Alessandria, Italy
| | - Angelica Zago
- Department of Radiology, Conegliano Hospital, Conegliano, Italy
| | | | - Fabio Canal
- Department of Pathology, Conegliano Hospital, Conegliano, Italy
| | - Armando Serao
- Department of Surgery, Section of Urology, SS Antonio and Biagio and Cesare Arrigo Hospital, Via Venezia, 16, 15121, Alessandria, Italy
| | | | - Salvatore Valerio
- Department of Surgery, Section of Urology, Conegliano Hospital, Conegliano, Italy
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17
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Capuano I, Buonanno P, Riccio E, Crocetto F, Pisani A. Parapelvic Cysts: An Imaging Marker of Kidney Disease Potentially Leading to the Diagnosis of Treatable Rare Genetic Disorders? A Narrative Review of the Literature. J Nephrol 2022; 35:2035-2046. [PMID: 35749008 DOI: 10.1007/s40620-022-01375-0] [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: 01/06/2022] [Accepted: 06/02/2022] [Indexed: 11/25/2022]
Abstract
Simple renal cysts are a common finding during abdominal imaging assessment. The incidence increases with age and it is higher in male gender. Parapelvic cysts are a subset of simple cysts that arise within the renal parenchyma, adjacent to the renal sinus, characterized by being generally single, larger, and incompletely surrounded by renal parenchyma. Noteworthy, parapelvic cysts are a rare and understudied condition which, although considered clinically insignificant due to the absence of influence on renal function, still have a controversial aetiopathogenesis. On the other hand, urological management and differential diagnosis have been thoroughly investigated. The aim of our review is to provide an overall vision on this rare condition, usually misdiagnosed and underestimated, on the basis of more recent data. An accurate differential diagnosis of parapelvic cysts can lead to the identification of treatable conditions such as Fabry disease, autosomal dominant polycystic kidney disease, polycystic liver disease and tuberous sclerosis complex disease.
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Affiliation(s)
- Ivana Capuano
- Department of Public Health, Chair of Nephrology "Federico II", University of Naples, Via Sergio Pansini, 5, 80131, Naples, Italy.
| | - Pasquale Buonanno
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, University of Naples "Federico II", Naples, Italy
| | - Eleonora Riccio
- Institute for Biomedical Research and Innovation, National Research Council of Italy, Palermo, Italy
| | - Felice Crocetto
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, University of Naples "Federico II", Naples, Italy
| | - Antonio Pisani
- Department of Public Health, Chair of Nephrology "Federico II", University of Naples, Via Sergio Pansini, 5, 80131, Naples, Italy
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18
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French AFU Cancer Committee Guidelines - Update 2022-2024: management of kidney cancer. Prog Urol 2022; 32:1195-1274. [DOI: 10.1016/j.purol.2022.07.146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2022] [Revised: 07/14/2022] [Accepted: 07/18/2022] [Indexed: 11/17/2022]
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19
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Tian J, Teng F, Xu H, Zhang D, Chi Y, Zhang H. Systematic review and meta-analysis of multiparametric MRI clear cell likelihood scores for classification of small renal masses. Front Oncol 2022; 12:1004502. [DOI: 10.3389/fonc.2022.1004502] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Accepted: 10/11/2022] [Indexed: 11/13/2022] Open
Abstract
PurposeTo systematically assess the multiparametric MRI clear cell likelihood score (ccLS) algorithm for the classification of small renal masses (SRM).MethodsWe conducted an electronic literature search on Web of Science, MEDLINE (Ovid and PubMed), Cochrane Library, EMBASE, and Google Scholar to identify relevant articles from 2017 up to June 30, 2022. We included studies reporting the diagnostic performance of the ccLS for characterization of solid SRM. The bivariate model and hierarchical summary receiver operating characteristic (HSROC) model were used to pool sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR−), and diagnostic odds ratio (DOR). The quality evaluation was performed with the Quality Assessment of Diagnostic Accuracy Studies-2 tool.ResultsA total of 6 studies with 825 renal masses (785 patients) were included in the current meta-analysis. The pooled sensitivity and specificity for cT1a renal masses were 0.80 (95% CI 0.75–0.85) and 0.74 (95% CI 0.65–0.81) at the threshold of ccLS ≥4, the pooled LR+, LR−, and DOR were 3.04 (95% CI 2.34-3.95), 0.27 (95% CI 0.22–0.33), and 11.4 (95% CI 8.2-15.9), respectively. The area under the HSROC curve was 0.84 (95% CI 0.81–0.87). For all cT1 renal masses, the pooled sensitivity and specificity were 0.80 (95% CI 0.74–0.85) and 0.76 (95% CI 0.67–0.83).ConclusionsThe ccLS had moderate to high accuracy for identifying ccRCC from other RCC subtypes and with a moderate inter-reader agreement. However, its diagnostic performance remain needs multi-center, large cohort studies to validate in the future.
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Zhang Q, Dai X, Li W. Diagnostic performance of the Bosniak classification, version 2019 for cystic renal masses: A systematic review and meta-analysis. Front Oncol 2022; 12:931592. [PMID: 36330503 PMCID: PMC9623069 DOI: 10.3389/fonc.2022.931592] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 09/26/2022] [Indexed: 12/02/2022] Open
Abstract
Purpose To systematically assess the diagnostic performance of the Bosniak classification, version 2019 for risk stratification of cystic renal masses. Methods We conducted an electronic literature search on Web of Science, MEDLINE (Ovid and PubMed), Cochrane Library, EMBASE, and Google Scholar to identify relevant articles between June 1, 2019 and March 31, 2022 that used the Bosniak classification, version 2019 for risk stratification of cystic renal masses. Summary estimates of sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR−), and diagnostic odds ratio (DOR) were pooled with the bivariate model and hierarchical summary receiver operating characteristic (HSROC) model. The quality of the included studies was assessed with the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Results A total of eight studies comprising 720 patients were included. The pooled sensitivity and specificity were 0.85 (95% CI 0.79–0.90) and 0.68 (95% CI 0.58–0.76), respectively, for the class III/IV threshold, with a calculated area under the HSROC curve of 0.84 (95% CI 0.81–0.87). The pooled LR+, LR−, and DOR were 2.62 (95% CI 2.0–3.44), 0.22 (95% CI 0.16–0.32), and 11.7 (95% CI 6.8–20.0), respectively. The Higgins I2 statistics demonstrated substantial heterogeneity across studies, with an I2 of 57.8% for sensitivity and an I2 of 74.6% for specificity. In subgroup analyses, the pooled sensitivity and specificity for CT were 0.86 and 0.71, respectively, and those for MRI were 0.87 and 0.67, respectively. In five studies providing a head-to-head comparison between the two versions of the Bosniak classification, the 2019 version demonstrated significantly higher specificity (0.62 vs. 0.41, p < 0.001); however, it came at the cost of a significant decrease in sensitivity (0.88 vs. 0.94, p = 0.001). Conclusions The Bosniak classification, version 2019 demonstrated moderate sensitivity and specificity, and there was no difference in diagnostic accuracy between CT and MRI. Compared to version 2005, the Bosniak classification, version 2019 has the potential to significantly reduce overtreatment, but at the cost of a substantial decline in sensitivity.
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Zeng SE, Du MY, Yu Y, Huang SY, Zhang D, Cui XW, Dietrich CF. Ultrasound, CT, and MR Imaging for Evaluation of Cystic Renal Masses. JOURNAL OF ULTRASOUND IN MEDICINE : OFFICIAL JOURNAL OF THE AMERICAN INSTITUTE OF ULTRASOUND IN MEDICINE 2022; 41:807-819. [PMID: 34101225 DOI: 10.1002/jum.15762] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 05/12/2021] [Accepted: 05/23/2021] [Indexed: 06/12/2023]
Abstract
Cystic renal masses are often encountered during abdominal imaging. Although most of them are benign simple cysts, some cystic masses have malignant characteristics. The Bosniak classification system provides a useful way to classify cystic masses. The Bosniak classification is based on the results of a well-established computed tomography protocol. Over the past 30 years, the classification system has been refined and improved. This paper reviews the literature on this topic and compares the advantages and disadvantages of different screening and classification methods. Patients will benefit from multimodal diagnosis for lesions that are difficult to classify after a single examination.
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Affiliation(s)
- Shu-E Zeng
- Department of Ultrasound Medicine, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ming-Yue Du
- Department of Ultrasound Medicine, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yang Yu
- Department of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shu-Yan Huang
- Department of Ultrasound, The First People's Hospital of Huaihua, Huaihua, China
| | - Di Zhang
- Department of Medical Ultrasound, Affiliated Hospital of Nantong University, Nantong, China
| | - Xin-Wu Cui
- Department of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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[Modern tomography imaging techniques in urological diseases]. Urologe A 2022; 61:374-383. [PMID: 35262753 DOI: 10.1007/s00120-022-01792-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/08/2022] [Indexed: 10/18/2022]
Abstract
BACKGROUND Radiologic imaging is important for the detection, staging and follow-up of urological tumors. Basic therapy decisions for both oncological (surgical vs. systemic therapy, e.g. in testicular cancer) and non-oncological pathologies (interventional vs. conservative therapy, e.g. for ureteral stones) depend largely on the tomographic imaging performed. Due to its almost ubiquitous availability, speed and cost-effectiveness, computed tomography (CT) plays an important role not only in the clarification of abdominal trauma and non-traumatic emergencies, but also in staging and follow-up of oncological patients. However, the level of radiation exposure, impaired renal function and allergies to iodinated contrast media limit the use of CT. Magnetic resonance imaging (MRI) can be a good alternative for many areas of application in oncological and non-oncological imaging due to its high soft tissue differentiation and functional-specific protocols but without the use of ionizing radiation. AIM In the following, the main indications of abdominal and pelvic CT and MRI in urology and their limitations are summarized. RESULTS The areas of application between CT and MRI are increasingly overlapping, since the latest developments in CT continue to further reduce radiation exposure and increase contrast information, while the speed and robustness of MRI are significantly improving at the same time.
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Büttner T, Ritter M. Sonographie von Nieren, Retroperitoneum und Harnblase. Urologe A 2022; 61:357-364. [DOI: 10.1007/s00120-022-01791-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/07/2022] [Indexed: 10/18/2022]
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Cullivan O, Wong R, Albu C, D'Arcy F, O'Malley E, McCarthy P, Dowling CM. Assessment of the workload and financial burden of Bosniak IIF renal cyst surveillance in a tertiary referral hospital. Ir J Med Sci 2022; 191:2771-2775. [PMID: 35037159 PMCID: PMC8761533 DOI: 10.1007/s11845-022-02919-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Accepted: 01/01/2022] [Indexed: 11/12/2022]
Abstract
Background The Bosniak classification is a CT classification which stratifies renal cysts based on imaging appearances and therefore associated risk of malignancy. Bosniak IIf cysts are renal which have complex features and therefore require surveillance. Aims The aim of this study is to assess the economic and workload burden of diagnosing and following up Bosniak IIf cysts on the urology service in a tertiary hospital in the West of Ireland. Methods All patients with a diagnosis of Bosniak IIf renal cysts attending our urology service between 1st of January 2012 and 31st December 2020 were analysed. The following data were collected: number and modality of follow up scans, number of MDT discussions, number and type of outpatient appointments, surgical intervention, and length of follow up. Financial data were provided by the hospital finance department. Results One hundred and sixty-two patients were included. Total cost of follow up was €164,056, costing €1,012.7 per patient. Cost of outpatient visits was €77,850. Follow-up length ranged from 1 to 109 months, median follow up time 17.5 months. Overall cost of imaging was €74,518. There were a total of 80 MDT discussions at an overall cost of €11,688. Conclusions This study demonstrates that surveillance of patients with Bosniak IIf renal cysts represents a significant burden upon both radiology and urology services. Surveillance for these patients could be streamlined in the future through a number of initiatives such as virtual OPDs and dedicated MDTs.
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Affiliation(s)
- Orla Cullivan
- Department of Urology, Galway University Hospital, Galway, Ireland.
| | - Ruby Wong
- Department of Urology, Galway University Hospital, Galway, Ireland
| | - Cristian Albu
- Department of Urology, Galway University Hospital, Galway, Ireland
| | - Frank D'Arcy
- Department of Urology, Galway University Hospital, Galway, Ireland
| | - Eoin O'Malley
- Department of Radiology, Galway University Hospital, Galway, Ireland
| | - Peter McCarthy
- Department of Radiology, Galway University Hospital, Galway, Ireland
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Shahrouki P, Felker ER, Raman SS, Jeong WK, Lu DS, Finn JP. Steady-state ferumoxytol-enhanced MRI: early observations in benign abdominal organ masses and clinical implications. Abdom Radiol (NY) 2022; 47:460-470. [PMID: 34689252 PMCID: PMC8776683 DOI: 10.1007/s00261-021-03271-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Revised: 09/02/2021] [Accepted: 09/03/2021] [Indexed: 12/12/2022]
Abstract
INTRODUCTION The off-label use of ferumoxytol as a vascular MR imaging agent is growing rapidly. However, the properties of ferumoxytol suggest that it may play an important role in the detection and characterization of abdominal mass lesions. METHODS Thirty-six patients with benign abdominal mass lesions who underwent MR angiography with ferumoxytol also had T2-weighted HASTE imaging and fat-suppressed 3D T1-weighted imaging. The T1 and T2 enhancement characteristics of the lesions were analyzed and correlated with other imaging modalities and/or surgical findings and/or clinical follow-up. RESULTS In all patients with benign masses in the liver (n = 22 patients), spleen (n = 6 patients), kidneys (n = 33 patients), adrenal (n = 2 patients) and pancreas (n = 4 patients), based on the enhancement characteristics with ferumoxytol, readers were confident of the benign nature of the lesions and their conclusions were consistent with correlative imaging, tissue sampling and follow-up. One patient with a suspicious enhancing 2F Bosniak renal cyst had renal cell carcinoma confirmed on biopsy. CONCLUSION Ferumoxytol-enhanced MRI can increase diagnostic confidence for benign abdominal masses and can increase the conspicuity of mass lesions, relative to unenhanced MRI.
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Affiliation(s)
- Puja Shahrouki
- Department of Radiological Sciences, University of California Los Angeles, 757 Westwood Plaza, Los Angeles, CA 90095 USA
- Diagnostic Cardiovascular Imaging Laboratory, University of California Los Angeles, Peter V. Ueberroth Building Suite 3371, 10945 Le Conte Ave., Los Angeles, CA 90095 USA
| | - Ely R. Felker
- Department of Radiological Sciences, University of California Los Angeles, 757 Westwood Plaza, Los Angeles, CA 90095 USA
| | - Steven S. Raman
- Department of Radiological Sciences, University of California Los Angeles, 757 Westwood Plaza, Los Angeles, CA 90095 USA
| | - Woo Kyoung Jeong
- Department of Radiological Sciences, University of California Los Angeles, 757 Westwood Plaza, Los Angeles, CA 90095 USA
- Department of Radiology and Imaging Sciences, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro Gangnam-gu, Seoul, 06351 Republic of Korea
| | - David S. Lu
- Department of Radiological Sciences, University of California Los Angeles, 757 Westwood Plaza, Los Angeles, CA 90095 USA
| | - J. Paul Finn
- Department of Radiological Sciences, University of California Los Angeles, 757 Westwood Plaza, Los Angeles, CA 90095 USA
- Diagnostic Cardiovascular Imaging Laboratory, University of California Los Angeles, Peter V. Ueberroth Building Suite 3371, 10945 Le Conte Ave., Los Angeles, CA 90095 USA
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Schieda N, Krishna S, Pedrosa I, Kaffenberger SD, Davenport MS, Silverman SG. Active Surveillance of Renal Masses: The Role of Radiology. Radiology 2021; 302:11-24. [PMID: 34812670 DOI: 10.1148/radiol.2021204227] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Active surveillance of renal masses, which includes serial imaging with the possibility of delayed treatment, has emerged as a viable alternative to immediate therapeutic intervention in selected patients. Active surveillance is supported by evidence that many benign masses are resected unnecessarily, and treatment of small cancers has not substantially reduced cancer-specific mortality. These data are a call to radiologists to improve the diagnosis of benign renal masses and differentiate cancers that are biologically aggressive (prompting treatment) from those that are indolent (allowing treatment deferral). Current evidence suggests that active surveillance results in comparable cancer-specific survival with a low risk of developing metastasis. Radiology is central in this. Imaging is used at the outset to estimate the probability of malignancy and degree of aggressiveness in malignant masses and to follow up masses for growth and morphologic change. Percutaneous biopsy is used to provide a more definitive histologic diagnosis and to guide treatment decisions, including whether active surveillance is appropriate. Emerging applications that may improve imaging assessment of renal masses include standardized assessment of cystic and solid masses and radiomic analysis. This article reviews the current and future role of radiology in the care of patients with renal masses undergoing active surveillance.
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Affiliation(s)
- Nicola Schieda
- From the Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, 1053 Carling Ave, Ottawa, ON, Canada K1H 1H6 (N.S.); Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital and Women's College Hospital, University of Toronto, Toronto, Canada (S.K.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); Departments of Urology (S.D.K., M.S.D.) and Radiology (M.S.D.), Michigan Medicine, University of Michigan, Ann Arbor, Mich; and Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (S.G.S.)
| | - Satheesh Krishna
- From the Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, 1053 Carling Ave, Ottawa, ON, Canada K1H 1H6 (N.S.); Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital and Women's College Hospital, University of Toronto, Toronto, Canada (S.K.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); Departments of Urology (S.D.K., M.S.D.) and Radiology (M.S.D.), Michigan Medicine, University of Michigan, Ann Arbor, Mich; and Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (S.G.S.)
| | - Ivan Pedrosa
- From the Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, 1053 Carling Ave, Ottawa, ON, Canada K1H 1H6 (N.S.); Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital and Women's College Hospital, University of Toronto, Toronto, Canada (S.K.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); Departments of Urology (S.D.K., M.S.D.) and Radiology (M.S.D.), Michigan Medicine, University of Michigan, Ann Arbor, Mich; and Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (S.G.S.)
| | - Samuel D Kaffenberger
- From the Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, 1053 Carling Ave, Ottawa, ON, Canada K1H 1H6 (N.S.); Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital and Women's College Hospital, University of Toronto, Toronto, Canada (S.K.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); Departments of Urology (S.D.K., M.S.D.) and Radiology (M.S.D.), Michigan Medicine, University of Michigan, Ann Arbor, Mich; and Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (S.G.S.)
| | - Matthew S Davenport
- From the Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, 1053 Carling Ave, Ottawa, ON, Canada K1H 1H6 (N.S.); Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital and Women's College Hospital, University of Toronto, Toronto, Canada (S.K.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); Departments of Urology (S.D.K., M.S.D.) and Radiology (M.S.D.), Michigan Medicine, University of Michigan, Ann Arbor, Mich; and Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (S.G.S.)
| | - Stuart G Silverman
- From the Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, 1053 Carling Ave, Ottawa, ON, Canada K1H 1H6 (N.S.); Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital and Women's College Hospital, University of Toronto, Toronto, Canada (S.K.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); Departments of Urology (S.D.K., M.S.D.) and Radiology (M.S.D.), Michigan Medicine, University of Michigan, Ann Arbor, Mich; and Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (S.G.S.)
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Shampain KL, Shankar PR, Troost JP, Galantowicz ML, Pampati RA, Schoenheit TR, Shlensky DA, Barkmeier D, Curci NE, Kaza RK, Khalatbari S, Davenport MS. Interrater Agreement of Bosniak Classification Version 2019 and Version 2005 for Cystic Renal Masses at CT and MRI. Radiology 2021; 302:357-366. [PMID: 34726535 PMCID: PMC8805658 DOI: 10.1148/radiol.2021210853] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Background The Bosniak classification system for cystic renal masses was updated in 2019 in part to improve agreement compared with the 2005 version. Purpose To compare and investigate interrater agreement of Bosniak version 2019 and Bosniak version 2005 at CT and MRI. Materials and Methods In this retrospective single-center study, a blinded eight-reader assessment was performed in which 195 renal masses prospectively considered Bosniak IIF-IV (95 at CT, 100 at MRI, from 2006 to 2019 with version 2005) were re-evaluated with Bosniak versions 2019 and 2005. Radiologists (four faculty members, four residents) who were blinded to the initial clinical reading and histopathologic findings assessed all feature components and reported the overall Bosniak class for each system independently. Agreement was assessed with Gwet agreement coefficients. Uni- and multivariable linear regression models were developed to identify predictors of dispersion in the final Bosniak class assignment that could inform system refinement. Results A total of 185 patients were included (mean age, 63 years ± 13 [standard deviation]; 118 men). Overall interrater agreement was similar between Bosniak version 2019 and version 2005 (Gwet agreement coefficient: 0.51 [95% CI: 0.45, 0.57] vs 0.46 [95% CI: 0.42, 0.51]). This was true for experts (0.54 vs 0.49) and novices (0.50 vs 0.47) and at CT (0.56 vs 0.51) and MRI (0.52 vs 0.43). Nine percent of masses prospectively considered cystic using Bosniak version 2005 criteria were considered solid using version 2019 criteria. In general, masses were more commonly classified in lower categories when radiologists used Bosniak version 2019 criteria compared with version 2005 criteria. The sole predictor of dispersion in Bosniak version 2019 class assignment was dispersion in septa or wall quality (ie, smooth vs irregular thickening vs nodule; 72% [MRI] and 60% [CT] overall model variance explained; multivariable P < .001). Conclusion Overall interrater agreement was similar between Bosniak version 2019 and version 2005; disagreements in septa or wall quality were common and strongly predictive of variation in Bosniak class assignment. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Eberhardt in this issue.
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Affiliation(s)
- Kimberly L. Shampain
- From the University of Michigan, 1500 E Medical Center Dr, Room B2 A209A, Ann Arbor, MI 48109-5030
| | - Prasad R. Shankar
- From the University of Michigan, 1500 E Medical Center Dr, Room B2 A209A, Ann Arbor, MI 48109-5030
| | - Jonathan P. Troost
- From the University of Michigan, 1500 E Medical Center Dr, Room B2 A209A, Ann Arbor, MI 48109-5030
| | - Maarten L. Galantowicz
- From the University of Michigan, 1500 E Medical Center Dr, Room B2 A209A, Ann Arbor, MI 48109-5030
| | - Rudra A. Pampati
- From the University of Michigan, 1500 E Medical Center Dr, Room B2 A209A, Ann Arbor, MI 48109-5030
| | - Taylor R. Schoenheit
- From the University of Michigan, 1500 E Medical Center Dr, Room B2 A209A, Ann Arbor, MI 48109-5030
| | - David A. Shlensky
- From the University of Michigan, 1500 E Medical Center Dr, Room B2 A209A, Ann Arbor, MI 48109-5030
| | - Daniel Barkmeier
- From the University of Michigan, 1500 E Medical Center Dr, Room B2 A209A, Ann Arbor, MI 48109-5030
| | - Nicole E. Curci
- From the University of Michigan, 1500 E Medical Center Dr, Room B2 A209A, Ann Arbor, MI 48109-5030
| | - Ravi K. Kaza
- From the University of Michigan, 1500 E Medical Center Dr, Room B2 A209A, Ann Arbor, MI 48109-5030
| | - Shokoufeh Khalatbari
- From the University of Michigan, 1500 E Medical Center Dr, Room B2 A209A, Ann Arbor, MI 48109-5030
| | - Matthew S. Davenport
- From the University of Michigan, 1500 E Medical Center Dr, Room B2 A209A, Ann Arbor, MI 48109-5030
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Surgical outcomes of robot-assisted laparoscopic partial nephrectomy for cystic renal cell carcinoma. J Robot Surg 2021; 16:649-654. [PMID: 34342799 DOI: 10.1007/s11701-021-01292-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Accepted: 07/31/2021] [Indexed: 10/20/2022]
Abstract
To compare the surgical outcomes of robot-assisted partial nephrectomy (RAPN) between patients with cystic renal cell carcinoma (cRCC) and those with solid RCC (sRCC). We retrospectively analyzed 1065 patients who underwent RAPN between 2013 and 2020 for a pathological diagnosis of RCC. Patients were divided into two groups: cRCC and sRCC. cRCC was diagnosed according to the Bosniak classification system. To minimize selection bias between the two groups, patient variables (patient characteristics) and tumor factors (such as size and complexity) were adjusted using 1:1 propensity score matching. Of the 1065 patients, 94 (9%) were diagnosed with cRCC. Bosniak categories of IIF, III, and IV were noted in 4 (4.2%), 31 (33%), and 59 (63%) patients, respectively. After matching, 83 patients each were assigned to the cRCC and sRCC groups. The operation time in cRCC tended to be longer than in sRCC but not significantly different (164 vs. 150 min, P = 0.0767). Other surgical outcomes, such as change in estimated glomerular filtration rate ( - 5.2 vs. - 7.2%, P = 0.1577), perioperative complications (14.5 vs. 15.7%, P = 0.9225), estimated blood loss (62 vs. 58 mL, P = 0.5613), or negative surgical margin status (100 vs 99%, P = 0.236), were not significantly different between the two groups. During the follow-up period of about 2 years, one and two patients showed recurrence in the cRCC and sRCC groups, respectively. The surgical outcomes of RAPN were similar between cRCC and sRCC, demonstrating the feasibility of RAPN for cRCC.
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Sidhu PS, Graumann O, Webb J. Is CEUS the future for imaging complex renal cysts? Are we on the threshold of a change? ULTRASCHALL IN DER MEDIZIN (STUTTGART, GERMANY : 1980) 2021; 42:344-346. [PMID: 34344055 DOI: 10.1055/a-1511-9997] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
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Xia Q, Yuan X, Huang M, Zhou X, Zhou Z. Contrast-enhanced Ultrasound for Diagnosis of Renal Cystic Mass. Curr Med Imaging 2021; 18:292-298. [PMID: 34825641 DOI: 10.2174/1573405617666210719141831] [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: 02/17/2021] [Revised: 05/30/2021] [Accepted: 06/02/2021] [Indexed: 11/22/2022]
Abstract
BACKGROUND Cystic Renal Cell Carcinoma (CRCC) is often challenging to differentiate from complex cysts with sonographic manifestations of renal carcinoma. Contrast-Enhanced Ultrasound (CEUS) is a new technology, and its clinical utility in the diagnosis of renal cystic mass has not been established. OBJECTIVE To analyze the characteristics of CEUS of renal cystic masses and to explore the clinical significance and value of CEUS in the diagnosis of CRCC. METHODS This study was a retrospective study. A total of 32 cystic masses from January 2018 to December 2019 were selected. The images of conventional ultrasound (US) and CEUS were confirmed via surgical pathology. The routine US was used to observe the location, shape, size, boundary, cyst wall, internal echo, and blood supply of each cystic mass. CEUS observed contrast enhancement of the cyst wall, cystic septa, and solid nodules of cystic masses. RESULTS There were 26 cases of CRCC, 5 cases of renal cysts, and 1 case of renal tuberculosis. The enhancement pattern, degree of enhancement, and pseudocapsular sign by CEUS in benign and malignant masses had statistically significant differences (P<.05). In the diagnosis of CRCC, the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 92.3%, 83.3%, 90.6%, 96.0%, and 71.4% for CEUS; 57.6%, 66.7%, 59.3%, 88.2%, and 26.7% for conventional US, respectively. CEUS had a higher sensitivity and accuracy than the conventional US (P<.05). However, the diagnostic specificity, positive predictive value, and negative predictive value of the two methods were not significantly different (P>.05). CONCLUSION CEUS is more accurate in the diagnosis of renal cystic masses, and it can be used as an effective imaging method.
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Affiliation(s)
- Qingqing Xia
- Department of Ultrasound, The First Affiliated Hospital of Nanchang University. China
| | - Xinchun Yuan
- Department of Ultrasound, The First Affiliated Hospital of Nanchang University, No. 17 YongWai Zheng Street, Nanchang 330006. China
| | - Meifeng Huang
- Department of Ultrasound, The First Affiliated Hospital of Nanchang University. China
| | - Xiling Zhou
- Department of Ultrasound, The First Affiliated Hospital of Nanchang University. China
| | - Zhiyu Zhou
- College of Traditional Chinese Medicine, Jiangxi University of Traditional Chinese Medicine, Nanchang 330004. China
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Value of Quantitative CTTA in Differentiating Malignant From Benign Bosniak III Renal Lesions on CT Images. J Comput Assist Tomogr 2021; 45:528-536. [PMID: 34176873 DOI: 10.1097/rct.0000000000001181] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
OBJECTIVE The aim of this study was to investigate whether computed tomography texture analysis can differentiate malignant from benign Bosniak III renal lesions on computed tomography (CT) images. METHODS This retrospective case-control study included 45 patients/lesions (22 benign and 23 malignant lesions) with Bosniak III renal lesions who underwent CT examination. Axial image slices in the unenhanced phase, corticomedullary phase, and nephrographic phase were selected and delineated manually. Computed tomography texture analysis was performed on each lesion during these 3 phases. Histogram-based, gray-level co-occurrence matrix, and gray-level run-length matrix features were extracted using open-source software and analyzed. In addition, receiver operating characteristic curve was constructed, and the area under the receiver operating characteristic curve (AUC) of each feature was constructed. RESULTS Of the 33 extracted features, 16 features showed significant differences (P < 0.05). Eight features were significantly different between the 2 groups after Holm-Bonferroni correction, including 3 histogram-based, 4 gray-level co-occurrence matrix, and 1 gray-level run-length matrix features (P < 0.01). The texture features resulted in the highest AUC of 0.769 ± 0.074. Renal cell carcinomas were labeled with a higher degree of lesion gray-level disorder and lower lesion homogeneity, and a model incorporating the 3 most discriminative features resulted in an AUC of 0.846 ± 0.058. CONCLUSIONS The results of this study showed that CT texture features were related to malignancy in Bosniak III renal lesions. Computed tomography texture analysis might help in differentiating malignant from benign Bosniak III renal lesions on CT images.
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Alabousi M, Wilson E, Al-Ghetaa RK, Patlas MN. General Review on the Current Management of Incidental Findings on Cross-Sectional Imaging: What Guidelines to Use, How to Follow Them, and Management and Medical-Legal Considerations. Radiol Clin North Am 2021; 59:501-509. [PMID: 34053601 DOI: 10.1016/j.rcl.2021.03.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
"Incidentalomas" are a common part of daily practice for radiologists, and knowledge of appropriate management guidelines is important in ensuring that no potentially clinically relevant findings are missed or are lost to follow-up in asymptomatic patients. Incidental findings of the brain, spine, thyroid, lungs, breasts, liver, adrenals, spleen, pancreas, kidneys, bowel, and ovaries are discussed, including where to find guidelines for management recommendations, how to follow them, and medical-legal considerations.
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Affiliation(s)
- Mostafa Alabousi
- Department of Radiology, McMaster University, 1280 Main St W, Hamilton, ON L8S 4L8, Canada.
| | - Evan Wilson
- Department of Radiology, McMaster University, 1280 Main St W, Hamilton, ON L8S 4L8, Canada
| | - Rayeh Kashef Al-Ghetaa
- Institute of Health Policy, Management and Evaluation, University of Toronto, 155 College St 4th Floor, Toronto, ON M5T 3M6, Canada
| | - Michael N Patlas
- Department of Radiology, McMaster University, Hamilton General Hospital, 237 Barton St E, Hamilton, ON L8L 2X2, Canada
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Bosniak Classification of Cystic Renal Masses Version 2019: Comparison to Version 2005 for Class Distribution, Diagnostic Performance, and Interreader Agreement Using CT and MRI. AJR Am J Roentgenol 2021; 217:1367-1376. [PMID: 34076460 DOI: 10.2214/ajr.21.25796] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Background: The Bosniak classification system for cystic renal masses (CRMs) was updated in 2019, requiring further investigation. Objective: To compare version 2005 and version 2019 of the Bosniak classification system in terms of class distribution, diagnostic performance, inter-reader agreement, and inter-modality agreement between CT and MRI. Methods: This retrospective study included 100 patients (mean age, 52.4±11.6 years; 68 men, 32 women) with 104 CRMs (74 malignant) who underwent CT, MRI, and resection between 2010 and 2019. Two radiologists independently evaluated CRMs in separate sessions for each combination of version and modality and assigned a Bosniak class. Diagnostic performance was compared using McNemar tests. Inter-reader and inter-modality agreement were analyzed using weighted kappa coefficients. Results: Across readers and modalities, proportion of class IIF was higher for version 2019 than version 2005 (reader 1: 28.8%-30.8% vs 6.7%-12.5%; reader 2: 26.0%-28.8% vs 8.7%-19.2%), although 95% CIs overlapped for reader 2 on CT. Proportion of class III was lower for version 2019 than version 2005 (reader 1: 33.7%-35.6% vs 49%-51.9%; reader 2: 31.7%-40.4% vs 37.5%-52.9%), although 95% CIs overlapped for all comparisons. Version 2019 demonstrated lower sensitivity for malignancy than version 2005 across readers and modalities (all p<.05); for example, using CT, sensitivity was 75.7% for both readers with version 2019, versus 85.1%-87.8% with version 2005. However, version 2019 demonstrated higher specificity than version 2005, which was significant (all p<.05) for reader 1 For example, using CT, specificity was 73.3% (reader 1) and 70.0% (reader 2) with version 2019, versus 50.0% (reader 1) and 56.7% (reader 2) with version 2005. Diagnostic accuracy was not different between versions (version 2005: 76.9%-85.6%; version 2019: 74.0%-78.8%). Inter-reader and inter- modality agreement were substantial for version 2005 (κ=0.676-0.782; 0.711-0.723) and version 2019 (κ=0.756-0.804; 0.704-0.781). Conclusion: Version 2019, versus version 2005, results in shift in CRM assignment from class III to class IIF. Version 2019 results in lower sensitivity, higher specificity, and similar accuracy versus version 2005. Inter-reader and inter-modality agreement are similar between versions. Clinical impact: Version 2019 facilitates recommending imaging surveillance for more CRMs.
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Yan JH, Chan J, Osman H, Munir J, Alrasheed S, Flood TA, Schieda N. Bosniak Classification version 2019: validation and comparison to original classification in pathologically confirmed cystic masses. Eur Radiol 2021; 31:9579-9587. [PMID: 34019130 DOI: 10.1007/s00330-021-08006-5] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Revised: 04/06/2021] [Accepted: 04/20/2021] [Indexed: 11/28/2022]
Abstract
OBJECTIVE To evaluate Bosniak Classification v2019 definitions in pathologically confirmed cystic renal masses. MATERIALS AND METHODS Seventy-three cystic (≤ 25% solid) masses with histological confirmation (57 malignant, 16 benign) imaged by CT (N = 28) or CT+MRI (N = 56) between 2009 and 2019 were independently evaluated by three blinded radiologists using Bosniak v2019 and original classifications. Discrepancies were resolved by consensus with a fourth blinded radiologist. Overall class and v2019 features were compared to pathology. RESULTS Inter-observer agreement was slightly improved comparing v2019 to Original Bosniak Classification (kappa = 0.26-0.47 versus 0.24-0.34 respectively). v2019 proportion of IIF and III masses (20.5% [15/73, 95% confidence interval (CI) 12.0-31.6%], 38.6% [28/73, 95% CI 27.2-50.5%]) differed from the original classification (6.8% [5/73, 95% CI 2.3-15.3%], 61.6% [45/73, 95% CI 49.5-72.8%]) with overlapping proportion of malignancy in each class. Mean septa number (7 ± 4 [range 1-10]) was not associated with malignancy (p = 0.89). Mean wall and septa thicknesses were 3 ± 3 (1-14) and 3 ± 2 (1-10) mm and higher in malignancies (p = 0.03 and 0.20 respectively). Areas under the receiver-operator-characteristic curve for wall and septa thickness were 0.66 (95% CI 0.54-0.79) and 0.61 (95% CI 0.45-0.78) with an optimal cut point of ≥ 3 mm (sensitivity 33.3%, specificity 86.7% and sensitivity 53%, specificity 73% respectively). Proportion of malignancy occurring in masses with the v2019 features "irregularity" (76.9% [10/13], 95% CI 46.2-94.9%) and "nodule" (89.7% [26/29], 95% CI 72.7-97.8%) overlapped. Angle of "nodule" (p = 0.27) was not associated with malignancy. CONCLUSION Bosniak v2019 definitions for wall/septa thickness and protrusions are associated with malignancy. Overall, Bosniak v2019 categorizes a higher proportion of malignant masses in Class IIF with slight improvement in inter-observer agreement. KEY POINTS • Considering Bosniak v2019 Class IIF cystic masses with many (≥ 4) smooth and thin septa, there was no association between the number of septa and malignancy (p = 0.89) in this study. • Increased cyst wall and septa thickness are associated with malignancy and a lower threshold of ≥ 3 mm maximized overall diagnostic accuracy compared to ≥ 4 mm threshold proposed for Bosniak v2019 Class 3. • An overlapping proportion of malignant masses is noted in Bosniak v2019 Class 3 masses with "irregularity" (76.9% [10/13], 95% CI 46.2-94.9%) compared to Bosniak v2019 Class 4 masses with "nodule" (89.7% [26/29], 95% CI 72.7-97.8%).
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Affiliation(s)
- Jin Hui Yan
- Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, Ottawa, ON, Canada
| | - Jason Chan
- Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, Ottawa, ON, Canada
| | - Heba Osman
- Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, Ottawa, ON, Canada
| | - Javeria Munir
- Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, Ottawa, ON, Canada
| | - Sumaya Alrasheed
- Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, Ottawa, ON, Canada
| | - Trevor A Flood
- Department of Anatomical Pathology, The Ottawa Hospital, University of Ottawa, Ottawa, ON, Canada
| | - Nicola Schieda
- Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, Ottawa, ON, Canada.
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Prospective Comparison of Contrast-Enhanced Ultrasound and Magnetic Resonance Imaging to Computer Tomography for the Evaluation of Complex Cystic Renal Lesions. Urology 2021; 154:320-325. [PMID: 33984367 DOI: 10.1016/j.urology.2021.04.032] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Revised: 04/13/2021] [Accepted: 04/26/2021] [Indexed: 12/17/2022]
Abstract
OBJECTIVE To prospectively evaluate the diagnostic accuracy of contrast enhanced ultrasound (CEUS) and MRI compared to computed tomography (CT) as the current gold standard for the characterization of cystic renal lesions using the Bosniak classification. METHODS Between July 2014 and October 2017 we prospectively enrolled patients with cystic renal lesions. Based on the Bosniak classification of complex renal lesions (≥BII-F) we evaluated the accuracy of observed agreement by Cohen's Kappa coefficient and calculated sensitivity, specificity, positive and negative predictive values (PPV/NPV) between the three imaging modalities CT, MRI and CEUS. RESULTS We evaluated 65 cystic renal lesions in 48 patients (median age 63 years, range 36-91 years; 18 females, 30 males). According to CT 29 (47%) of the cystic renal lesions were classified as complex. The agreement between CEUS and CT in the classification of complex cystic lesions was fair (agreement 50.8%, Kappa 0.31), and was excellent between MRI and CT (agreement 93.9%, Kappa 0.88). Compared to CT, CEUS and MRI had a sensitivity of 100% and 96.6%, a specificity of 33.3% and 91.7%, a PPV of 54.7% and 90.3%, and a NPV of 100% and 97.1% with an accuracy of 63.1% and 93.8% respectively. CONCLUSION CEUS has an excellent sensitivity and NPV and represents a promising non-invasive screening tool for renal cystic lesions. The classification of complex renal cysts based on MRI and CT scans correlated closely.
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Siegel CL, Cohan R. Invited Commentary: Use of Bosniak Classification, Version 2019 in Clinical Practice. Radiographics 2021; 41:E75-E76. [PMID: 33871304 DOI: 10.1148/rg.2021210013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Cary Lynn Siegel
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (C.L.S.); and Department of Radiology, Michigan Medicine, University of Michigan, Ann Arbor, Mich (R.C.)
| | - Richard Cohan
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, St Louis, MO 63110 (C.L.S.); and Department of Radiology, Michigan Medicine, University of Michigan, Ann Arbor, Mich (R.C.)
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Schieda N, Davenport MS, Krishna S, Edney EA, Pedrosa I, Hindman N, Baroni RH, Curci NE, Shinagare A, Silverman SG. Bosniak Classification of Cystic Renal Masses, Version 2019: A Pictorial Guide to Clinical Use. Radiographics 2021; 41:814-828. [PMID: 33861647 DOI: 10.1148/rg.2021200160] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Cystic renal masses are commonly encountered in clinical practice. In 2019, the Bosniak classification of cystic renal masses, originally developed for CT, underwent a major revision to incorporate MRI and is referred to as the Bosniak Classification, version 2019. The proposed changes attempt to (a) define renal masses (ie, cystic tumors with less than 25% enhancing tissue) to which the classification should be applied; (b) emphasize specificity for diagnosis of cystic renal cancers, thereby decreasing the number of benign and indolent cystic masses that are unnecessarily treated or imaged further; (c) improve interobserver agreement by defining imaging features, terms, and classes of cystic renal masses; (d) reduce variation in reported malignancy rates for each of the Bosniak classes; (e) incorporate MRI and to some extent US; and (f) be applicable to all cystic renal masses encountered in clinical practice, including those that had been considered indeterminate with the original classification. The authors instruct how, using CT, MRI, and to some extent US, the revised classification can be applied, with representative clinical examples and images. Practical tips, pitfalls to avoid, and decision tree rules are included to help radiologists and other physicians apply the Bosniak Classification, version 2019 and better manage cystic renal masses. An online resource and mobile application are also available for clinical assistance. An invited commentary by Siegel and Cohan is available online. ©RSNA, 2021.
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Affiliation(s)
- Nicola Schieda
- From the Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, 1053 Carling Ave, Ottawa, ON, Canada K1H 1H6 (N.S.); Departments of Radiology (M.S.D., N.E.C.) and Urology (M.S.D.), Michigan Medicine, University of Michigan, Ann Arbor, Mich; Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital and Women's College Hospital, University of Toronto, Toronto, ON, Canada (S.K.); Department of Radiology, University of Nebraska Medical Center, Omaha, Neb (E.A.E.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); Department of Radiology, New York University Langone Medical Center, New York, NY (N.H.); Department of Radiology and Diagnostic Imaging, Hospital Israelita Albert Einstein, São Paulo, Brazil (R.H.B.); Department of Radiology, Brigham and Women's Hospital/Dana-Farber Cancer Institute, Harvard Medical School, Boston, Mass (A.S.); and Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (S.G.S.)
| | - Matthew S Davenport
- From the Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, 1053 Carling Ave, Ottawa, ON, Canada K1H 1H6 (N.S.); Departments of Radiology (M.S.D., N.E.C.) and Urology (M.S.D.), Michigan Medicine, University of Michigan, Ann Arbor, Mich; Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital and Women's College Hospital, University of Toronto, Toronto, ON, Canada (S.K.); Department of Radiology, University of Nebraska Medical Center, Omaha, Neb (E.A.E.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); Department of Radiology, New York University Langone Medical Center, New York, NY (N.H.); Department of Radiology and Diagnostic Imaging, Hospital Israelita Albert Einstein, São Paulo, Brazil (R.H.B.); Department of Radiology, Brigham and Women's Hospital/Dana-Farber Cancer Institute, Harvard Medical School, Boston, Mass (A.S.); and Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (S.G.S.)
| | - Satheesh Krishna
- From the Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, 1053 Carling Ave, Ottawa, ON, Canada K1H 1H6 (N.S.); Departments of Radiology (M.S.D., N.E.C.) and Urology (M.S.D.), Michigan Medicine, University of Michigan, Ann Arbor, Mich; Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital and Women's College Hospital, University of Toronto, Toronto, ON, Canada (S.K.); Department of Radiology, University of Nebraska Medical Center, Omaha, Neb (E.A.E.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); Department of Radiology, New York University Langone Medical Center, New York, NY (N.H.); Department of Radiology and Diagnostic Imaging, Hospital Israelita Albert Einstein, São Paulo, Brazil (R.H.B.); Department of Radiology, Brigham and Women's Hospital/Dana-Farber Cancer Institute, Harvard Medical School, Boston, Mass (A.S.); and Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (S.G.S.)
| | - Elizabeth A Edney
- From the Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, 1053 Carling Ave, Ottawa, ON, Canada K1H 1H6 (N.S.); Departments of Radiology (M.S.D., N.E.C.) and Urology (M.S.D.), Michigan Medicine, University of Michigan, Ann Arbor, Mich; Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital and Women's College Hospital, University of Toronto, Toronto, ON, Canada (S.K.); Department of Radiology, University of Nebraska Medical Center, Omaha, Neb (E.A.E.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); Department of Radiology, New York University Langone Medical Center, New York, NY (N.H.); Department of Radiology and Diagnostic Imaging, Hospital Israelita Albert Einstein, São Paulo, Brazil (R.H.B.); Department of Radiology, Brigham and Women's Hospital/Dana-Farber Cancer Institute, Harvard Medical School, Boston, Mass (A.S.); and Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (S.G.S.)
| | - Ivan Pedrosa
- From the Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, 1053 Carling Ave, Ottawa, ON, Canada K1H 1H6 (N.S.); Departments of Radiology (M.S.D., N.E.C.) and Urology (M.S.D.), Michigan Medicine, University of Michigan, Ann Arbor, Mich; Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital and Women's College Hospital, University of Toronto, Toronto, ON, Canada (S.K.); Department of Radiology, University of Nebraska Medical Center, Omaha, Neb (E.A.E.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); Department of Radiology, New York University Langone Medical Center, New York, NY (N.H.); Department of Radiology and Diagnostic Imaging, Hospital Israelita Albert Einstein, São Paulo, Brazil (R.H.B.); Department of Radiology, Brigham and Women's Hospital/Dana-Farber Cancer Institute, Harvard Medical School, Boston, Mass (A.S.); and Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (S.G.S.)
| | - Nicole Hindman
- From the Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, 1053 Carling Ave, Ottawa, ON, Canada K1H 1H6 (N.S.); Departments of Radiology (M.S.D., N.E.C.) and Urology (M.S.D.), Michigan Medicine, University of Michigan, Ann Arbor, Mich; Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital and Women's College Hospital, University of Toronto, Toronto, ON, Canada (S.K.); Department of Radiology, University of Nebraska Medical Center, Omaha, Neb (E.A.E.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); Department of Radiology, New York University Langone Medical Center, New York, NY (N.H.); Department of Radiology and Diagnostic Imaging, Hospital Israelita Albert Einstein, São Paulo, Brazil (R.H.B.); Department of Radiology, Brigham and Women's Hospital/Dana-Farber Cancer Institute, Harvard Medical School, Boston, Mass (A.S.); and Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (S.G.S.)
| | - Ronaldo H Baroni
- From the Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, 1053 Carling Ave, Ottawa, ON, Canada K1H 1H6 (N.S.); Departments of Radiology (M.S.D., N.E.C.) and Urology (M.S.D.), Michigan Medicine, University of Michigan, Ann Arbor, Mich; Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital and Women's College Hospital, University of Toronto, Toronto, ON, Canada (S.K.); Department of Radiology, University of Nebraska Medical Center, Omaha, Neb (E.A.E.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); Department of Radiology, New York University Langone Medical Center, New York, NY (N.H.); Department of Radiology and Diagnostic Imaging, Hospital Israelita Albert Einstein, São Paulo, Brazil (R.H.B.); Department of Radiology, Brigham and Women's Hospital/Dana-Farber Cancer Institute, Harvard Medical School, Boston, Mass (A.S.); and Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (S.G.S.)
| | - Nicole E Curci
- From the Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, 1053 Carling Ave, Ottawa, ON, Canada K1H 1H6 (N.S.); Departments of Radiology (M.S.D., N.E.C.) and Urology (M.S.D.), Michigan Medicine, University of Michigan, Ann Arbor, Mich; Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital and Women's College Hospital, University of Toronto, Toronto, ON, Canada (S.K.); Department of Radiology, University of Nebraska Medical Center, Omaha, Neb (E.A.E.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); Department of Radiology, New York University Langone Medical Center, New York, NY (N.H.); Department of Radiology and Diagnostic Imaging, Hospital Israelita Albert Einstein, São Paulo, Brazil (R.H.B.); Department of Radiology, Brigham and Women's Hospital/Dana-Farber Cancer Institute, Harvard Medical School, Boston, Mass (A.S.); and Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (S.G.S.)
| | - Atul Shinagare
- From the Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, 1053 Carling Ave, Ottawa, ON, Canada K1H 1H6 (N.S.); Departments of Radiology (M.S.D., N.E.C.) and Urology (M.S.D.), Michigan Medicine, University of Michigan, Ann Arbor, Mich; Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital and Women's College Hospital, University of Toronto, Toronto, ON, Canada (S.K.); Department of Radiology, University of Nebraska Medical Center, Omaha, Neb (E.A.E.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); Department of Radiology, New York University Langone Medical Center, New York, NY (N.H.); Department of Radiology and Diagnostic Imaging, Hospital Israelita Albert Einstein, São Paulo, Brazil (R.H.B.); Department of Radiology, Brigham and Women's Hospital/Dana-Farber Cancer Institute, Harvard Medical School, Boston, Mass (A.S.); and Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (S.G.S.)
| | - Stuart G Silverman
- From the Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, 1053 Carling Ave, Ottawa, ON, Canada K1H 1H6 (N.S.); Departments of Radiology (M.S.D., N.E.C.) and Urology (M.S.D.), Michigan Medicine, University of Michigan, Ann Arbor, Mich; Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital and Women's College Hospital, University of Toronto, Toronto, ON, Canada (S.K.); Department of Radiology, University of Nebraska Medical Center, Omaha, Neb (E.A.E.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (I.P.); Department of Radiology, New York University Langone Medical Center, New York, NY (N.H.); Department of Radiology and Diagnostic Imaging, Hospital Israelita Albert Einstein, São Paulo, Brazil (R.H.B.); Department of Radiology, Brigham and Women's Hospital/Dana-Farber Cancer Institute, Harvard Medical School, Boston, Mass (A.S.); and Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (S.G.S.)
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Cantisani V, Bertolotto M, Clevert DA, Correas JM, Drudi FM, Fischer T, Gilja OH, Granata A, Graumann O, Harvey CJ, Ignee A, Jenssen C, Lerchbaumer MH, Ragel M, Saftoiu A, Serra AL, Stock KF, Webb J, Sidhu PS. EFSUMB 2020 Proposal for a Contrast-Enhanced Ultrasound-Adapted Bosniak Cyst Categorization - Position Statement. ULTRASCHALL IN DER MEDIZIN (STUTTGART, GERMANY : 1980) 2021; 42:154-166. [PMID: 33307594 DOI: 10.1055/a-1300-1727] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
The well-established Bosniak renal cyst classification is based on contrast-enhanced computed tomography determining the malignant potential of cystic renal lesions. Ultrasound has not been incorporated into this pathway. However, the development of ultrasound contrast agents coupled with the superior resolution of ultrasound makes it possible to redefine the imaging of cystic renal lesions. In this position statement, an EFSUMB Expert Task Force reviews, analyzes, and describes the accumulated knowledge and limitations and presents the current position on the use of ultrasound contrast agents in the evaluation of cystic renal lesions.
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Affiliation(s)
- Vito Cantisani
- Department of Radiology, "Sapienza" University of Rome, Rome, Italy
| | - Michele Bertolotto
- Department of Radiology, University of Trieste, Ospedale di Cattinara, Trieste, IT
| | - Dirk-André Clevert
- Department of Clinical Radiology, University of Munich-Großhadern Campus, Munich, Germany
| | - Jean-Michel Correas
- Service de Radiologie adultes, Hôpital Necker, Université Paris Descartes, Paris, France
| | | | - Thomas Fischer
- Department of Radiology, University Berlin, Charité, Berlin, Germany
| | - Odd Helge Gilja
- Haukeland University Hospital, National Centre for Ultrasound in Gastroenterology, Bergen, Norway
| | - Antonio Granata
- Nephrology and Dialysis Unit, Emergency Hospital "Cannizzaro", Catania - Italy
| | - Ole Graumann
- Research and Innovation Unit of Radiology, University of Southern Denmark, Odense C, Denmark
| | - Christopher J Harvey
- Department of Imaging, Imperial College NHS Healthcare Trust, London, United Kingdom of Great Britain and Northern Ireland
| | - Andre Ignee
- Innere Medizin 2, Caritas-Krankenhaus, Bad Mergentheim, Germany
| | - Christian Jenssen
- Klinik für Innere Medizin, Krankenhaus Märkisch Oderland Strausberg/Wriezen, Germany
| | - Markus Herbert Lerchbaumer
- Department of Radiology, Charité Centrum 6 - Diagnostische und interventionelle Radiologie und Nuklearmedizin, Berlin, Germany
| | - Matthew Ragel
- Radiology Department, Aintree University Hospitals NHS Foundation Trust, Liverpool, United Kingdom of Great Britain and Northern Ireland
| | - Adrian Saftoiu
- Research Center in Gastroenterology and Hepatology, University of Medicine and Pharmacy Craiova, Romania
| | - Andreas L Serra
- Department of Internal Medicine and Nephrology, Klinik Hirslanden, Zürich, Switzerland
| | | | - Jolanta Webb
- Radiology Department, Aintree University Hospitals NHS Foundation Trust, Liverpool, United Kingdom of Great Britain and Northern Ireland
| | - Paul S Sidhu
- Department of Radiology, King's College Hospital London, United Kingdom of Great Britain and Northern Ireland
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Scialpi M, Vitale ME, Gallo E, Nicola R. MRI-based Bosniak Version 2019 for IIF Masses: Improved Classification by Subtraction Imaging. Radiology 2021; 299:E250. [PMID: 33754830 DOI: 10.1148/radiol.2021204059] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Michele Scialpi
- Division of Diagnostic Imaging, Department of Surgical and Biomedical Sciences, Santa Maria della Misericordia Hospital, University of Perugia, S. Andrea delle Fratte, 06159 Perugia, Italy, e-mail:
| | - Maria Emanuela Vitale
- Division of Diagnostic Imaging, Department of Surgical and Biomedical Sciences, Santa Maria della Misericordia Hospital, University of Perugia, S. Andrea delle Fratte, 06159 Perugia, Italy, e-mail:
| | - Elena Gallo
- Division of Diagnostic Imaging, Department of Surgical and Biomedical Sciences, Santa Maria della Misericordia Hospital, University of Perugia, S. Andrea delle Fratte, 06159 Perugia, Italy, e-mail:
| | - Refky Nicola
- Department of Radiology, Roswell Park Cancer Institute, Buffalo, NY
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Nicolau C, Antunes N, Paño B, Sebastia C. Imaging Characterization of Renal Masses. ACTA ACUST UNITED AC 2021; 57:medicina57010051. [PMID: 33435540 PMCID: PMC7827903 DOI: 10.3390/medicina57010051] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Revised: 12/28/2020] [Accepted: 01/04/2021] [Indexed: 01/10/2023]
Abstract
The detection of a renal mass is a relatively frequent occurrence in the daily practice of any Radiology Department. The diagnostic approaches depend on whether the lesion is cystic or solid. Cystic lesions can be managed using the Bosniak classification, while management of solid lesions depends on whether the lesion is well-defined or infiltrative. The approach to well-defined lesions focuses mainly on the differentiation between renal cancer and benign tumors such as angiomyolipoma (AML) and oncocytoma. Differential diagnosis of infiltrative lesions is wider, including primary and secondary malignancies and inflammatory disease, and knowledge of the patient history is essential. Radiologists may establish a possible differential diagnosis based on the imaging features of the renal masses and the clinical history. The aim of this review is to present the contribution of the different imaging techniques and image guided biopsies in the diagnostic management of cystic and solid renal lesions.
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Affiliation(s)
- Carlos Nicolau
- Radiology Department, Hospital Clinic, University of Barcelona (UB), 08036 Barcelona, Spain; (B.P.); (C.S.)
- Correspondence:
| | - Natalie Antunes
- Radiology Department, Hospital de Santa Marta, 1169-024 Lisboa, Portugal;
| | - Blanca Paño
- Radiology Department, Hospital Clinic, University of Barcelona (UB), 08036 Barcelona, Spain; (B.P.); (C.S.)
| | - Carmen Sebastia
- Radiology Department, Hospital Clinic, University of Barcelona (UB), 08036 Barcelona, Spain; (B.P.); (C.S.)
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EFFICACY OF PERCUTANEOUS DRAINING OPERATIONS FOR SIMPLE RENAL CYSTS. WORLD OF MEDICINE AND BIOLOGY 2021. [DOI: 10.26724/2079-8334-2021-4-78-146-149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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Bosniak Classification of Cystic Renal Masses Version 2019: Comparison of Categorization Using CT and MRI. AJR Am J Roentgenol 2020; 216:412-420. [PMID: 32755181 DOI: 10.2214/ajr.20.23656] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
BACKGROUND. Bosniak classification version 2019 proposed refinements for cystic renal mass characterization and now formally incorporates MRI, which may improve concordance with CT. OBJECTIVE. The purpose of this study is to compare concordance of CT and MRI in evaluation of cystic renal masses using Bosniak classification version 2019. METHODS. Three abdominal radiologists retrospectively reviewed 68 consecutive cystic renal masses from 45 patients assessed with both CT and MRI renal mass protocols within a year between 2005 and 2019. CT and MRI were reviewed independently and in separate sessions, using both the original and 2019 versions of Bosniak classification systems. RESULTS. Using Bosniak classification version 2019, cystic renal masses were classified into 12 category I, 19 category II, 13 category IIF, four category III, and 20 category IV by CT and eight category I, 15 category II, 23 category IIF, nine category III, and 13 category IV by MRI. Among individual features, MRI showed more septa (p < 0.001, p = 0.046, p = 0.005; McNemar test) for all three radiologists, although both CT and MRI showed a similar number of protrusions (p = 0.823, p = 1.0, p = 0.302) and maximal septa and wall thickness (p = 1.0, p = 1.0, p = 0.145). Of the discordant cases with version 2019, MRI led to a higher categorization in 12 masses. The reason for upgrade was most commonly because of protrusions identified only on MRI (n = 4), an increased number of septa (n = 3), and a new category: heterogeneously T1-weighted hyperintensity (n = 3). Neither modality was more likely to lead to a categorization change for either version 2019 (p = 0.502; McNemar test) or the original (p = 0.823) Bosniak classification system. Overall interrater agreement was substantial for both CT (κ = 0.745) and MRI (κ = 0.655) using version 2019 and was slightly higher than that of the original system for CT (κ = 0.707) and MRI (κ = 0.623). CONCLUSION. CT and MRI were concordant in the majority of cases using Bosniak classification version 2019, and category changes by modality were not statistically significant. Interrater agreements were substantial for both CT and MRI. CLINICAL IMPACT. Bosniak classification version 2019 as applied to cystic renal masses has substantial interrater agreement and does not lead to systematic category upgrades with either CT or MRI.
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Hedegaard SF, Tolouee SA, Azawi NH. Multi-disciplinary team conference clarifies bosniak classification of complex renal cysts. Scand J Urol 2020; 55:78-82. [PMID: 33307952 DOI: 10.1080/21681805.2020.1857830] [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] [Indexed: 10/22/2022]
Abstract
OBJECTIVES The aims of this study are to determine the progression rate of Bosniak IIF cysts, the malignancy rates of complex renal cysts in patients undergoing surgery and explore the influence of multi-disciplinary team conference (MDT) on re-classification of Bosniak cysts. MATERIALS AND METHODS All CT scans from January 2010 to 2017 were pooled into a database. Initially, 167 patients were identified with possible Bosniak IIF, III or IV cysts. Patients with follow up of less than 24 months, without progression or regression were excluded. RESULTS Thirty-one (18.6%) cysts of the initial 167 cysts were either up or downgraded at a MDT. Twenty-six of the 31 cysts were up or downgraded at the primary MDT, 13 cysts (50%) were downgraded, five cysts (19.2%) were upgraded and eight cysts (30.8%) were re-classified as solid tumors. Of those 19/26 (73.1%) were primary interpreted by a periphery radiologist and re-classified centrally. The last five patients 5/120 cysts (4.2%) were re-classified during follow up. 116 patients with a total of 120 cysts met the inclusion criteria, 79 (65.8%) Bosniak IIF, 28 (23.3%) Bosniak III and 13 (10.8%) Bosniak IV cysts represented. Median follow up of Bosniak IIF cysts were 46 months. One Bosniak IIF cyst progressed to a solid tumor at 15 months from diagnosis, progression rate 1.3%. Histopathology was papillary renal cell carcinoma. Malignancy rates of Bosniak III and IV cysts were 50% and 78%, respectively. CONCLUSION Multi-disciplinary team conference may have an important role in correct classification of Bosniak cysts. TRIAL REGISTRATION None.
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Affiliation(s)
| | | | - Nessn H Azawi
- Department of Urology, Zealand University Hospital, Roskilde, Denmark.,Institute of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
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Lerchbaumer MH, Putz FJ, Rübenthaler J, Rogasch J, Jung EM, Clevert DA, Hamm B, Makowski M, Fischer T. Contrast-enhanced ultrasound (CEUS) of cystic renal lesions in comparison to CT and MRI in a multicenter setting. Clin Hemorheol Microcirc 2020; 75:419-429. [PMID: 32039837 DOI: 10.3233/ch-190764] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
PURPOSE Contrast-enhanced-ultrasound (CEUS) has been frequently used in assessment of cystic renal lesions. OBJECTIVE The aim of this study was to investigate the Bosniak classification in CEUS compared to CT and MRI in a multi-center setting. METHODS Bosniak classification in CEUS examinations of cystic renal lesions were compared to imaging findings in computed-tomography (ceCT) and magnetic-resonance-imaging (ceMRI). Imaging results were correlated to histopathological reports. All examinations were performed by experts (EFSUMB level 3) using up-to-date CEUS examination-protocols. RESULTS Overall, 173 cystic renal lesions were compared to subgroups CT (n = 87) and MRI (n = 86). Using Bosniak-classification 64/87 renal cysts (73.6%) were rated equal compared to CT with upgrade of four lesions (4.6%) and downgrade of 19 lesions (21.8%) by CT (Intra-class-correlation [ICC] coefficient of 0.824 [p < 0.001]). CEUS compared to MRI, presenting different scoring especially in classes Bosniak IIF (n = 16/31) and Bosniak III (n = 16/28) with an ICC coefficient of 0.651 (p < 0.001). CONCLUSION CEUS can visualize even finest septal and small nodular wall enhancement, which may result in an upgrade of cystic lesions into a higher Bosniak class compared to CT or MRI. Thus, a modification of the Bosniak classification on CEUS may reduce unnecessary biopsies and surgery.
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Affiliation(s)
- Markus Herbert Lerchbaumer
- Charité - Universitätsmedizin Berlin, Corporate Member of FreieUniversität Berlin, Humbold, Universitätzu Berlin, and Berlin Institute of Health, Department of Radiology, Berlin, Germany
| | - Franz Josef Putz
- Department of Nephrology, University Hospital Regensburg, Regensburg, Germany
| | - Johannes Rübenthaler
- Department of Radiology, Ludwig-Maximilians-University of Munich, Munich, Germany
| | - Julian Rogasch
- Charité - Universitätsmedizin Berlin, Corporate Member of FreieUniversität Berlin, Humbold, Universitätzu Berlin, and Berlin Institute of Health, Department of Nuclear Medicine, Berlin, Germany
| | - Ernst-Michael Jung
- Department of Radiology, University Medical Center Regensburg, Regensburg, Germany
| | - Dirk-Andre Clevert
- Department of Radiology, Ludwig-Maximilians-University of Munich, Munich, Germany
| | - Bernd Hamm
- Charité - Universitätsmedizin Berlin, Corporate Member of FreieUniversität Berlin, Humbold, Universitätzu Berlin, and Berlin Institute of Health, Department of Radiology, Berlin, Germany
| | - Marcus Makowski
- Charité - Universitätsmedizin Berlin, Corporate Member of FreieUniversität Berlin, Humbold, Universitätzu Berlin, and Berlin Institute of Health, Department of Radiology, Berlin, Germany
| | - Thomas Fischer
- Charité - Universitätsmedizin Berlin, Corporate Member of FreieUniversität Berlin, Humbold, Universitätzu Berlin, and Berlin Institute of Health, Department of Radiology, Berlin, Germany
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Bensalah K, Bigot P, Albiges L, Bernhard J, Bodin T, Boissier R, Correas J, Gimel P, Hetet J, Long J, Nouhaud F, Ouzaïd I, Rioux-Leclercq N, Méjean A. Recommandations françaises du Comité de cancérologie de l’AFU – actualisation 2020–2022 : prise en charge du cancer du rein. Prog Urol 2020; 30:S2-S51. [DOI: 10.1016/s1166-7087(20)30749-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
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Frumer M, Konen O, Shapira Rootman M, Soudack M, Ben-Shlush A, Ben-Meir D. The Modified Bosniak Classification for Intermediate-Risk Renal Cysts in Children. Urology 2020; 149:206-210. [PMID: 33129869 DOI: 10.1016/j.urology.2020.10.022] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Revised: 10/13/2020] [Accepted: 10/15/2020] [Indexed: 10/23/2022]
Abstract
OBJECTIVES To examine correlations of the modified Bosniak categories assigned by radiologists to histological results and inter-rater reliability, focusing on intermediate-risk lesions. MATERIALS AND METHODS The data of pediatric patients who underwent surgery for intermediate-risk complex renal cyst at a tertiary medical center in 2006-2019 were collected retrospectively. Four pediatric radiologists from 2 different medical centers reviewed the available imaging scans, and assigned each to one of the four modified Bosniak classification categories. Binary cohorts of the Bosniak categories (I-II vs III-IV) were compared to the histological results. Diagnostic accuracy (benign- vs intermediate-risk lesion) was calculated for each radiologist and for each imaging modality. Krippendorff's α test was used to measure inter-rater reliability. RESULTS The cohort included seven children, each with 1 complex cyst that was rated as intermediate-risk on pathological study. The median age was 1.5 years (IQR 1, 11.9). A correct classification was made in 41/56 imaging readings (sensitivity 73.2%). Applying Krippendorff's test to the binary Bosniak cohorts yielded poor inter-rater agreement (α = 0.08). CONCLUSION Implementation of the modified Bosniak classification in children caused a disconcerting underestimation of intermediate risk. There was a low inter-rater consistency for the categories intended to guide decisions regarding surgery or conservative management. The findings suggest that clinicians should be cautious using the modified Bosniak system for children.
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Affiliation(s)
- Michael Frumer
- Pediatric Urology Unit, Schneider Children's Medical Center of Israel, Petach Tikva, Israel.
| | - Osnat Konen
- Department of Diagnostic Imaging, Schneider Children's Medical Center of Israel, Petach Tikva, Israel; Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Mika Shapira Rootman
- Department of Diagnostic Imaging, Schneider Children's Medical Center of Israel, Petach Tikva, Israel; Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Michalle Soudack
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel; Department of Pediatric Imaging, The Edmond and Lily Safra Children's Hospital, Chaim Sheba Medical Center, Tel Hashomer, Ramat Gan, Israel
| | - Aviva Ben-Shlush
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel; Department of Pediatric Imaging, The Edmond and Lily Safra Children's Hospital, Chaim Sheba Medical Center, Tel Hashomer, Ramat Gan, Israel
| | - David Ben-Meir
- Pediatric Urology Unit, Schneider Children's Medical Center of Israel, Petach Tikva, Israel; Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
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Krishna S, Schieda N, Pedrosa I, Hindman N, Baroni RH, Silverman SG, Davenport MS. Update on MRI of Cystic Renal Masses Including Bosniak Version 2019. J Magn Reson Imaging 2020; 54:341-356. [PMID: 33009722 DOI: 10.1002/jmri.27364] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2020] [Revised: 08/27/2020] [Accepted: 08/28/2020] [Indexed: 12/15/2022] Open
Abstract
Incidental cystic renal masses are common, usually benign, and almost always indolent. Since 1986, the Bosniak classification has been used to express the risk of malignancy in a cystic renal mass detected at imaging. Historically, magnetic resonance imaging (MRI) was not included in that classification. The proposed Bosniak v.2019 update has formally incorporated MRI, included definitions of imaging terms designed to improve interobserver agreement and specificity for malignancy, and incorporated a variety of masses that were incompletely defined or not included in the original classification. For example, at unenhanced MRI, homogeneous masses markedly hyperintense at T2 -weighted imaging (similar to cerebrospinal fluid) and homogeneous masses markedly hyperintense at fat suppressed T1 -weighted imaging (approximately ≥2.5 times more intense than adjacent renal parenchyma) are classified as Bosniak II and may be safely ignored, even when they have not been imaged with a complete renal mass MRI protocol. MRI has specific advantages and is recommended to evaluate masses that at computed tomography (CT) 1) have abundant thick or nodular calcifications; 2) are homogeneous, hyperattenuating, ≥3 cm, and nonenhancing; or 3) are heterogeneous and nonenhancing. Although MRI is generally excellent for characterizing cystic renal masses, there are unique weaknesses of MRI that bear consideration. These details and others related to MRI of cystic renal masses are described in this review, with an emphasis on Bosniak v.2019. A website (https://bosniak-calculator.herokuapp.com/) and mobile phone apps named "Bosniak Calculator" have been developed for ease of assignment of Bosniak classes. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 3.
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Affiliation(s)
- Satheesh Krishna
- Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital and Women's College Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Nicola Schieda
- Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, Ottawa, Ontario, Canada
| | - Ivan Pedrosa
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Nicole Hindman
- Department of Radiology, New York University Langone Medical Center, New York, New York, USA
| | - Ronaldo H Baroni
- Department of Radiology and Diagnostic Imaging, Hospital Israelita Albert Einstein, São Paulo, Brazil
| | - Stuart G Silverman
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Matthew S Davenport
- Departments of Radiology and Urology, Michigan Medicine, University of Michigan, Ann Arbor, Michigan, USA
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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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Bai X, Sun SM, Xu W, Kang HH, Li L, Jin YQ, Gong QGL, Liang GC, Liu HY, Liu LL, Chen SL, Wang QR, Wu P, Guo AT, Huang QB, Zhang XJ, Ye HY, Wang HY. MRI-based Bosniak Classification of Cystic Renal Masses, Version 2019: Interobserver Agreement, Impact of Readers' Experience, and Diagnostic Performance. Radiology 2020; 297:597-605. [PMID: 32960726 DOI: 10.1148/radiol.2020200478] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Background The 2019 Bosniak classification (version 2019) of cystic renal masses (CRMs) provides a systematic update to the currently used 2005 Bosniak classification (version 2005). Further validation is required before widespread application. Purpose To evaluate the interobserver agreement of MRI criteria, the impact of readers' experience, and the diagnostic performance between version 2019 and version 2005. Materials and Methods From January 2009 to December 2018, consecutive patients with CRM who had undergone renal MRI and surgical-pathologic examination were included in this retrospective study. On the basis of version 2019 and version 2005, all CRMs were independently classified by eight radiologists with different levels of experience. By using multirater κ statistics, interobserver agreement was evaluated with comparisons between classifications and between senior and junior radiologists. Diagnostic performance between classifications by dichotomizing classes I-IV into lower (I-IIF) and higher (III-IV) classes was compared by using the McNemar test. P < .05 was considered to indicate a statistically significant difference. Results A total of 207 patients (mean age ± standard deviation, 49 years ± 12; 139 male and 68 female patients) with CRMs were included. Overall, interobserver agreement was higher with version 2019 than version 2005 (weighted κ = 0.64 vs 0.50, respectively; P < .001). Interobserver agreement between senior and junior radiologists did not differ between version 2019 (weighted κ = 0.65 vs 0.64, respectively; P = .71) and version 2005 (weighted κ = 0.54 vs 0.46; P < .001). Diagnostic specificity for malignancy was higher with version 2019 than with version 2005 (83% [92 of 111] vs 68% [75 of 111], respectively; P < .001), without any difference in sensitivity (89% [85 of 96] vs 84% [81 of 96]; P = .34). Conclusion In the updated Bosniak classification, interobserver agreement improved and was unaffected by observers' experience. The diagnostic performance with version 2019 was superior to that with version 2005, with higher specificity. Published under a CC BY 4.0 license. Online supplemental material is available for this article. See also the editorial by Choyke in this issue.
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Affiliation(s)
- Xu Bai
- From the Medical School of Chinese PLA, No. 28 Fuxing Rd, Haidian District, Beijing 100853, China (X.B., S.M.S., H.H.K.); Department of Radiology, First Medical Center, Chinese PLA General Hospital, Beijing, China (X.B., W.X., H.H.K., X.J.Z., H.Y.Y., H.Y.W.); Department of Health Service, Second Medical Center, Chinese PLA General Hospital, Beijing, China (S.M.S.); Department of Medical Statistic, Institute for Hospital Management Research, Chinese PLA General Hospital, Beijing, China (L.L.); Department of Radiology, Huaiyang County People's Hospital, Zhoukou, China (Y.Q.J.); Department of Radiology, Armed Police Corps Hospital of Henan Province, Zhengzhou, China (Q.G.L.G.); Department of Radiology, Zunhua Second Hospital, Zunhua, China (G.C.L.); Department of Radiology, Baoding Qingyuan District People's Hospital, Baoding, China (H.Y.L.); Department of Radiology, Beijing First Hospital of Integrated Chinese and Western Medicine, Beijing, China (L.L.L.); Department of Radiology, Seventh Medical Center, Chinese PLA General Hospital, Beijing, China (S.L.C.); Department of Radiology, The People's Hospital of Xishuangbanna Dai Nationality Autonomous Prefecture, Jinghong, China (Q.R.W.); Department of Radiology, First Affiliated Hospital of Hebei North University, Zhangjiakou, China (P.W.); Department of Pathology, First Medical Center, Chinese PLA General Hospital, Beijing, China (A.T.G.). Department of Urology, First Medical Center, Chinese PLA General Hospital, Beijing, China (Q.B.H.)
| | - Song-Mei Sun
- From the Medical School of Chinese PLA, No. 28 Fuxing Rd, Haidian District, Beijing 100853, China (X.B., S.M.S., H.H.K.); Department of Radiology, First Medical Center, Chinese PLA General Hospital, Beijing, China (X.B., W.X., H.H.K., X.J.Z., H.Y.Y., H.Y.W.); Department of Health Service, Second Medical Center, Chinese PLA General Hospital, Beijing, China (S.M.S.); Department of Medical Statistic, Institute for Hospital Management Research, Chinese PLA General Hospital, Beijing, China (L.L.); Department of Radiology, Huaiyang County People's Hospital, Zhoukou, China (Y.Q.J.); Department of Radiology, Armed Police Corps Hospital of Henan Province, Zhengzhou, China (Q.G.L.G.); Department of Radiology, Zunhua Second Hospital, Zunhua, China (G.C.L.); Department of Radiology, Baoding Qingyuan District People's Hospital, Baoding, China (H.Y.L.); Department of Radiology, Beijing First Hospital of Integrated Chinese and Western Medicine, Beijing, China (L.L.L.); Department of Radiology, Seventh Medical Center, Chinese PLA General Hospital, Beijing, China (S.L.C.); Department of Radiology, The People's Hospital of Xishuangbanna Dai Nationality Autonomous Prefecture, Jinghong, China (Q.R.W.); Department of Radiology, First Affiliated Hospital of Hebei North University, Zhangjiakou, China (P.W.); Department of Pathology, First Medical Center, Chinese PLA General Hospital, Beijing, China (A.T.G.). Department of Urology, First Medical Center, Chinese PLA General Hospital, Beijing, China (Q.B.H.)
| | - Wei Xu
- From the Medical School of Chinese PLA, No. 28 Fuxing Rd, Haidian District, Beijing 100853, China (X.B., S.M.S., H.H.K.); Department of Radiology, First Medical Center, Chinese PLA General Hospital, Beijing, China (X.B., W.X., H.H.K., X.J.Z., H.Y.Y., H.Y.W.); Department of Health Service, Second Medical Center, Chinese PLA General Hospital, Beijing, China (S.M.S.); Department of Medical Statistic, Institute for Hospital Management Research, Chinese PLA General Hospital, Beijing, China (L.L.); Department of Radiology, Huaiyang County People's Hospital, Zhoukou, China (Y.Q.J.); Department of Radiology, Armed Police Corps Hospital of Henan Province, Zhengzhou, China (Q.G.L.G.); Department of Radiology, Zunhua Second Hospital, Zunhua, China (G.C.L.); Department of Radiology, Baoding Qingyuan District People's Hospital, Baoding, China (H.Y.L.); Department of Radiology, Beijing First Hospital of Integrated Chinese and Western Medicine, Beijing, China (L.L.L.); Department of Radiology, Seventh Medical Center, Chinese PLA General Hospital, Beijing, China (S.L.C.); Department of Radiology, The People's Hospital of Xishuangbanna Dai Nationality Autonomous Prefecture, Jinghong, China (Q.R.W.); Department of Radiology, First Affiliated Hospital of Hebei North University, Zhangjiakou, China (P.W.); Department of Pathology, First Medical Center, Chinese PLA General Hospital, Beijing, China (A.T.G.). Department of Urology, First Medical Center, Chinese PLA General Hospital, Beijing, China (Q.B.H.)
| | - Huan-Huan Kang
- From the Medical School of Chinese PLA, No. 28 Fuxing Rd, Haidian District, Beijing 100853, China (X.B., S.M.S., H.H.K.); Department of Radiology, First Medical Center, Chinese PLA General Hospital, Beijing, China (X.B., W.X., H.H.K., X.J.Z., H.Y.Y., H.Y.W.); Department of Health Service, Second Medical Center, Chinese PLA General Hospital, Beijing, China (S.M.S.); Department of Medical Statistic, Institute for Hospital Management Research, Chinese PLA General Hospital, Beijing, China (L.L.); Department of Radiology, Huaiyang County People's Hospital, Zhoukou, China (Y.Q.J.); Department of Radiology, Armed Police Corps Hospital of Henan Province, Zhengzhou, China (Q.G.L.G.); Department of Radiology, Zunhua Second Hospital, Zunhua, China (G.C.L.); Department of Radiology, Baoding Qingyuan District People's Hospital, Baoding, China (H.Y.L.); Department of Radiology, Beijing First Hospital of Integrated Chinese and Western Medicine, Beijing, China (L.L.L.); Department of Radiology, Seventh Medical Center, Chinese PLA General Hospital, Beijing, China (S.L.C.); Department of Radiology, The People's Hospital of Xishuangbanna Dai Nationality Autonomous Prefecture, Jinghong, China (Q.R.W.); Department of Radiology, First Affiliated Hospital of Hebei North University, Zhangjiakou, China (P.W.); Department of Pathology, First Medical Center, Chinese PLA General Hospital, Beijing, China (A.T.G.). Department of Urology, First Medical Center, Chinese PLA General Hospital, Beijing, China (Q.B.H.)
| | - Lin Li
- From the Medical School of Chinese PLA, No. 28 Fuxing Rd, Haidian District, Beijing 100853, China (X.B., S.M.S., H.H.K.); Department of Radiology, First Medical Center, Chinese PLA General Hospital, Beijing, China (X.B., W.X., H.H.K., X.J.Z., H.Y.Y., H.Y.W.); Department of Health Service, Second Medical Center, Chinese PLA General Hospital, Beijing, China (S.M.S.); Department of Medical Statistic, Institute for Hospital Management Research, Chinese PLA General Hospital, Beijing, China (L.L.); Department of Radiology, Huaiyang County People's Hospital, Zhoukou, China (Y.Q.J.); Department of Radiology, Armed Police Corps Hospital of Henan Province, Zhengzhou, China (Q.G.L.G.); Department of Radiology, Zunhua Second Hospital, Zunhua, China (G.C.L.); Department of Radiology, Baoding Qingyuan District People's Hospital, Baoding, China (H.Y.L.); Department of Radiology, Beijing First Hospital of Integrated Chinese and Western Medicine, Beijing, China (L.L.L.); Department of Radiology, Seventh Medical Center, Chinese PLA General Hospital, Beijing, China (S.L.C.); Department of Radiology, The People's Hospital of Xishuangbanna Dai Nationality Autonomous Prefecture, Jinghong, China (Q.R.W.); Department of Radiology, First Affiliated Hospital of Hebei North University, Zhangjiakou, China (P.W.); Department of Pathology, First Medical Center, Chinese PLA General Hospital, Beijing, China (A.T.G.). Department of Urology, First Medical Center, Chinese PLA General Hospital, Beijing, China (Q.B.H.)
| | - Ye-Qiang Jin
- From the Medical School of Chinese PLA, No. 28 Fuxing Rd, Haidian District, Beijing 100853, China (X.B., S.M.S., H.H.K.); Department of Radiology, First Medical Center, Chinese PLA General Hospital, Beijing, China (X.B., W.X., H.H.K., X.J.Z., H.Y.Y., H.Y.W.); Department of Health Service, Second Medical Center, Chinese PLA General Hospital, Beijing, China (S.M.S.); Department of Medical Statistic, Institute for Hospital Management Research, Chinese PLA General Hospital, Beijing, China (L.L.); Department of Radiology, Huaiyang County People's Hospital, Zhoukou, China (Y.Q.J.); Department of Radiology, Armed Police Corps Hospital of Henan Province, Zhengzhou, China (Q.G.L.G.); Department of Radiology, Zunhua Second Hospital, Zunhua, China (G.C.L.); Department of Radiology, Baoding Qingyuan District People's Hospital, Baoding, China (H.Y.L.); Department of Radiology, Beijing First Hospital of Integrated Chinese and Western Medicine, Beijing, China (L.L.L.); Department of Radiology, Seventh Medical Center, Chinese PLA General Hospital, Beijing, China (S.L.C.); Department of Radiology, The People's Hospital of Xishuangbanna Dai Nationality Autonomous Prefecture, Jinghong, China (Q.R.W.); Department of Radiology, First Affiliated Hospital of Hebei North University, Zhangjiakou, China (P.W.); Department of Pathology, First Medical Center, Chinese PLA General Hospital, Beijing, China (A.T.G.). Department of Urology, First Medical Center, Chinese PLA General Hospital, Beijing, China (Q.B.H.)
| | - Qing-Ge-Le Gong
- From the Medical School of Chinese PLA, No. 28 Fuxing Rd, Haidian District, Beijing 100853, China (X.B., S.M.S., H.H.K.); Department of Radiology, First Medical Center, Chinese PLA General Hospital, Beijing, China (X.B., W.X., H.H.K., X.J.Z., H.Y.Y., H.Y.W.); Department of Health Service, Second Medical Center, Chinese PLA General Hospital, Beijing, China (S.M.S.); Department of Medical Statistic, Institute for Hospital Management Research, Chinese PLA General Hospital, Beijing, China (L.L.); Department of Radiology, Huaiyang County People's Hospital, Zhoukou, China (Y.Q.J.); Department of Radiology, Armed Police Corps Hospital of Henan Province, Zhengzhou, China (Q.G.L.G.); Department of Radiology, Zunhua Second Hospital, Zunhua, China (G.C.L.); Department of Radiology, Baoding Qingyuan District People's Hospital, Baoding, China (H.Y.L.); Department of Radiology, Beijing First Hospital of Integrated Chinese and Western Medicine, Beijing, China (L.L.L.); Department of Radiology, Seventh Medical Center, Chinese PLA General Hospital, Beijing, China (S.L.C.); Department of Radiology, The People's Hospital of Xishuangbanna Dai Nationality Autonomous Prefecture, Jinghong, China (Q.R.W.); Department of Radiology, First Affiliated Hospital of Hebei North University, Zhangjiakou, China (P.W.); Department of Pathology, First Medical Center, Chinese PLA General Hospital, Beijing, China (A.T.G.). Department of Urology, First Medical Center, Chinese PLA General Hospital, Beijing, China (Q.B.H.)
| | - Guo-Cheng Liang
- From the Medical School of Chinese PLA, No. 28 Fuxing Rd, Haidian District, Beijing 100853, China (X.B., S.M.S., H.H.K.); Department of Radiology, First Medical Center, Chinese PLA General Hospital, Beijing, China (X.B., W.X., H.H.K., X.J.Z., H.Y.Y., H.Y.W.); Department of Health Service, Second Medical Center, Chinese PLA General Hospital, Beijing, China (S.M.S.); Department of Medical Statistic, Institute for Hospital Management Research, Chinese PLA General Hospital, Beijing, China (L.L.); Department of Radiology, Huaiyang County People's Hospital, Zhoukou, China (Y.Q.J.); Department of Radiology, Armed Police Corps Hospital of Henan Province, Zhengzhou, China (Q.G.L.G.); Department of Radiology, Zunhua Second Hospital, Zunhua, China (G.C.L.); Department of Radiology, Baoding Qingyuan District People's Hospital, Baoding, China (H.Y.L.); Department of Radiology, Beijing First Hospital of Integrated Chinese and Western Medicine, Beijing, China (L.L.L.); Department of Radiology, Seventh Medical Center, Chinese PLA General Hospital, Beijing, China (S.L.C.); Department of Radiology, The People's Hospital of Xishuangbanna Dai Nationality Autonomous Prefecture, Jinghong, China (Q.R.W.); Department of Radiology, First Affiliated Hospital of Hebei North University, Zhangjiakou, China (P.W.); Department of Pathology, First Medical Center, Chinese PLA General Hospital, Beijing, China (A.T.G.). Department of Urology, First Medical Center, Chinese PLA General Hospital, Beijing, China (Q.B.H.)
| | - Hong-Yan Liu
- From the Medical School of Chinese PLA, No. 28 Fuxing Rd, Haidian District, Beijing 100853, China (X.B., S.M.S., H.H.K.); Department of Radiology, First Medical Center, Chinese PLA General Hospital, Beijing, China (X.B., W.X., H.H.K., X.J.Z., H.Y.Y., H.Y.W.); Department of Health Service, Second Medical Center, Chinese PLA General Hospital, Beijing, China (S.M.S.); Department of Medical Statistic, Institute for Hospital Management Research, Chinese PLA General Hospital, Beijing, China (L.L.); Department of Radiology, Huaiyang County People's Hospital, Zhoukou, China (Y.Q.J.); Department of Radiology, Armed Police Corps Hospital of Henan Province, Zhengzhou, China (Q.G.L.G.); Department of Radiology, Zunhua Second Hospital, Zunhua, China (G.C.L.); Department of Radiology, Baoding Qingyuan District People's Hospital, Baoding, China (H.Y.L.); Department of Radiology, Beijing First Hospital of Integrated Chinese and Western Medicine, Beijing, China (L.L.L.); Department of Radiology, Seventh Medical Center, Chinese PLA General Hospital, Beijing, China (S.L.C.); Department of Radiology, The People's Hospital of Xishuangbanna Dai Nationality Autonomous Prefecture, Jinghong, China (Q.R.W.); Department of Radiology, First Affiliated Hospital of Hebei North University, Zhangjiakou, China (P.W.); Department of Pathology, First Medical Center, Chinese PLA General Hospital, Beijing, China (A.T.G.). Department of Urology, First Medical Center, Chinese PLA General Hospital, Beijing, China (Q.B.H.)
| | - Lin-Lin Liu
- From the Medical School of Chinese PLA, No. 28 Fuxing Rd, Haidian District, Beijing 100853, China (X.B., S.M.S., H.H.K.); Department of Radiology, First Medical Center, Chinese PLA General Hospital, Beijing, China (X.B., W.X., H.H.K., X.J.Z., H.Y.Y., H.Y.W.); Department of Health Service, Second Medical Center, Chinese PLA General Hospital, Beijing, China (S.M.S.); Department of Medical Statistic, Institute for Hospital Management Research, Chinese PLA General Hospital, Beijing, China (L.L.); Department of Radiology, Huaiyang County People's Hospital, Zhoukou, China (Y.Q.J.); Department of Radiology, Armed Police Corps Hospital of Henan Province, Zhengzhou, China (Q.G.L.G.); Department of Radiology, Zunhua Second Hospital, Zunhua, China (G.C.L.); Department of Radiology, Baoding Qingyuan District People's Hospital, Baoding, China (H.Y.L.); Department of Radiology, Beijing First Hospital of Integrated Chinese and Western Medicine, Beijing, China (L.L.L.); Department of Radiology, Seventh Medical Center, Chinese PLA General Hospital, Beijing, China (S.L.C.); Department of Radiology, The People's Hospital of Xishuangbanna Dai Nationality Autonomous Prefecture, Jinghong, China (Q.R.W.); Department of Radiology, First Affiliated Hospital of Hebei North University, Zhangjiakou, China (P.W.); Department of Pathology, First Medical Center, Chinese PLA General Hospital, Beijing, China (A.T.G.). Department of Urology, First Medical Center, Chinese PLA General Hospital, Beijing, China (Q.B.H.)
| | - Si-Lu Chen
- From the Medical School of Chinese PLA, No. 28 Fuxing Rd, Haidian District, Beijing 100853, China (X.B., S.M.S., H.H.K.); Department of Radiology, First Medical Center, Chinese PLA General Hospital, Beijing, China (X.B., W.X., H.H.K., X.J.Z., H.Y.Y., H.Y.W.); Department of Health Service, Second Medical Center, Chinese PLA General Hospital, Beijing, China (S.M.S.); Department of Medical Statistic, Institute for Hospital Management Research, Chinese PLA General Hospital, Beijing, China (L.L.); Department of Radiology, Huaiyang County People's Hospital, Zhoukou, China (Y.Q.J.); Department of Radiology, Armed Police Corps Hospital of Henan Province, Zhengzhou, China (Q.G.L.G.); Department of Radiology, Zunhua Second Hospital, Zunhua, China (G.C.L.); Department of Radiology, Baoding Qingyuan District People's Hospital, Baoding, China (H.Y.L.); Department of Radiology, Beijing First Hospital of Integrated Chinese and Western Medicine, Beijing, China (L.L.L.); Department of Radiology, Seventh Medical Center, Chinese PLA General Hospital, Beijing, China (S.L.C.); Department of Radiology, The People's Hospital of Xishuangbanna Dai Nationality Autonomous Prefecture, Jinghong, China (Q.R.W.); Department of Radiology, First Affiliated Hospital of Hebei North University, Zhangjiakou, China (P.W.); Department of Pathology, First Medical Center, Chinese PLA General Hospital, Beijing, China (A.T.G.). Department of Urology, First Medical Center, Chinese PLA General Hospital, Beijing, China (Q.B.H.)
| | - Qing-Rong Wang
- From the Medical School of Chinese PLA, No. 28 Fuxing Rd, Haidian District, Beijing 100853, China (X.B., S.M.S., H.H.K.); Department of Radiology, First Medical Center, Chinese PLA General Hospital, Beijing, China (X.B., W.X., H.H.K., X.J.Z., H.Y.Y., H.Y.W.); Department of Health Service, Second Medical Center, Chinese PLA General Hospital, Beijing, China (S.M.S.); Department of Medical Statistic, Institute for Hospital Management Research, Chinese PLA General Hospital, Beijing, China (L.L.); Department of Radiology, Huaiyang County People's Hospital, Zhoukou, China (Y.Q.J.); Department of Radiology, Armed Police Corps Hospital of Henan Province, Zhengzhou, China (Q.G.L.G.); Department of Radiology, Zunhua Second Hospital, Zunhua, China (G.C.L.); Department of Radiology, Baoding Qingyuan District People's Hospital, Baoding, China (H.Y.L.); Department of Radiology, Beijing First Hospital of Integrated Chinese and Western Medicine, Beijing, China (L.L.L.); Department of Radiology, Seventh Medical Center, Chinese PLA General Hospital, Beijing, China (S.L.C.); Department of Radiology, The People's Hospital of Xishuangbanna Dai Nationality Autonomous Prefecture, Jinghong, China (Q.R.W.); Department of Radiology, First Affiliated Hospital of Hebei North University, Zhangjiakou, China (P.W.); Department of Pathology, First Medical Center, Chinese PLA General Hospital, Beijing, China (A.T.G.). Department of Urology, First Medical Center, Chinese PLA General Hospital, Beijing, China (Q.B.H.)
| | - Peng Wu
- From the Medical School of Chinese PLA, No. 28 Fuxing Rd, Haidian District, Beijing 100853, China (X.B., S.M.S., H.H.K.); Department of Radiology, First Medical Center, Chinese PLA General Hospital, Beijing, China (X.B., W.X., H.H.K., X.J.Z., H.Y.Y., H.Y.W.); Department of Health Service, Second Medical Center, Chinese PLA General Hospital, Beijing, China (S.M.S.); Department of Medical Statistic, Institute for Hospital Management Research, Chinese PLA General Hospital, Beijing, China (L.L.); Department of Radiology, Huaiyang County People's Hospital, Zhoukou, China (Y.Q.J.); Department of Radiology, Armed Police Corps Hospital of Henan Province, Zhengzhou, China (Q.G.L.G.); Department of Radiology, Zunhua Second Hospital, Zunhua, China (G.C.L.); Department of Radiology, Baoding Qingyuan District People's Hospital, Baoding, China (H.Y.L.); Department of Radiology, Beijing First Hospital of Integrated Chinese and Western Medicine, Beijing, China (L.L.L.); Department of Radiology, Seventh Medical Center, Chinese PLA General Hospital, Beijing, China (S.L.C.); Department of Radiology, The People's Hospital of Xishuangbanna Dai Nationality Autonomous Prefecture, Jinghong, China (Q.R.W.); Department of Radiology, First Affiliated Hospital of Hebei North University, Zhangjiakou, China (P.W.); Department of Pathology, First Medical Center, Chinese PLA General Hospital, Beijing, China (A.T.G.). Department of Urology, First Medical Center, Chinese PLA General Hospital, Beijing, China (Q.B.H.)
| | - Ai-Tao Guo
- From the Medical School of Chinese PLA, No. 28 Fuxing Rd, Haidian District, Beijing 100853, China (X.B., S.M.S., H.H.K.); Department of Radiology, First Medical Center, Chinese PLA General Hospital, Beijing, China (X.B., W.X., H.H.K., X.J.Z., H.Y.Y., H.Y.W.); Department of Health Service, Second Medical Center, Chinese PLA General Hospital, Beijing, China (S.M.S.); Department of Medical Statistic, Institute for Hospital Management Research, Chinese PLA General Hospital, Beijing, China (L.L.); Department of Radiology, Huaiyang County People's Hospital, Zhoukou, China (Y.Q.J.); Department of Radiology, Armed Police Corps Hospital of Henan Province, Zhengzhou, China (Q.G.L.G.); Department of Radiology, Zunhua Second Hospital, Zunhua, China (G.C.L.); Department of Radiology, Baoding Qingyuan District People's Hospital, Baoding, China (H.Y.L.); Department of Radiology, Beijing First Hospital of Integrated Chinese and Western Medicine, Beijing, China (L.L.L.); Department of Radiology, Seventh Medical Center, Chinese PLA General Hospital, Beijing, China (S.L.C.); Department of Radiology, The People's Hospital of Xishuangbanna Dai Nationality Autonomous Prefecture, Jinghong, China (Q.R.W.); Department of Radiology, First Affiliated Hospital of Hebei North University, Zhangjiakou, China (P.W.); Department of Pathology, First Medical Center, Chinese PLA General Hospital, Beijing, China (A.T.G.). Department of Urology, First Medical Center, Chinese PLA General Hospital, Beijing, China (Q.B.H.)
| | - Qing-Bo Huang
- From the Medical School of Chinese PLA, No. 28 Fuxing Rd, Haidian District, Beijing 100853, China (X.B., S.M.S., H.H.K.); Department of Radiology, First Medical Center, Chinese PLA General Hospital, Beijing, China (X.B., W.X., H.H.K., X.J.Z., H.Y.Y., H.Y.W.); Department of Health Service, Second Medical Center, Chinese PLA General Hospital, Beijing, China (S.M.S.); Department of Medical Statistic, Institute for Hospital Management Research, Chinese PLA General Hospital, Beijing, China (L.L.); Department of Radiology, Huaiyang County People's Hospital, Zhoukou, China (Y.Q.J.); Department of Radiology, Armed Police Corps Hospital of Henan Province, Zhengzhou, China (Q.G.L.G.); Department of Radiology, Zunhua Second Hospital, Zunhua, China (G.C.L.); Department of Radiology, Baoding Qingyuan District People's Hospital, Baoding, China (H.Y.L.); Department of Radiology, Beijing First Hospital of Integrated Chinese and Western Medicine, Beijing, China (L.L.L.); Department of Radiology, Seventh Medical Center, Chinese PLA General Hospital, Beijing, China (S.L.C.); Department of Radiology, The People's Hospital of Xishuangbanna Dai Nationality Autonomous Prefecture, Jinghong, China (Q.R.W.); Department of Radiology, First Affiliated Hospital of Hebei North University, Zhangjiakou, China (P.W.); Department of Pathology, First Medical Center, Chinese PLA General Hospital, Beijing, China (A.T.G.). Department of Urology, First Medical Center, Chinese PLA General Hospital, Beijing, China (Q.B.H.)
| | - Xiao-Jing Zhang
- From the Medical School of Chinese PLA, No. 28 Fuxing Rd, Haidian District, Beijing 100853, China (X.B., S.M.S., H.H.K.); Department of Radiology, First Medical Center, Chinese PLA General Hospital, Beijing, China (X.B., W.X., H.H.K., X.J.Z., H.Y.Y., H.Y.W.); Department of Health Service, Second Medical Center, Chinese PLA General Hospital, Beijing, China (S.M.S.); Department of Medical Statistic, Institute for Hospital Management Research, Chinese PLA General Hospital, Beijing, China (L.L.); Department of Radiology, Huaiyang County People's Hospital, Zhoukou, China (Y.Q.J.); Department of Radiology, Armed Police Corps Hospital of Henan Province, Zhengzhou, China (Q.G.L.G.); Department of Radiology, Zunhua Second Hospital, Zunhua, China (G.C.L.); Department of Radiology, Baoding Qingyuan District People's Hospital, Baoding, China (H.Y.L.); Department of Radiology, Beijing First Hospital of Integrated Chinese and Western Medicine, Beijing, China (L.L.L.); Department of Radiology, Seventh Medical Center, Chinese PLA General Hospital, Beijing, China (S.L.C.); Department of Radiology, The People's Hospital of Xishuangbanna Dai Nationality Autonomous Prefecture, Jinghong, China (Q.R.W.); Department of Radiology, First Affiliated Hospital of Hebei North University, Zhangjiakou, China (P.W.); Department of Pathology, First Medical Center, Chinese PLA General Hospital, Beijing, China (A.T.G.). Department of Urology, First Medical Center, Chinese PLA General Hospital, Beijing, China (Q.B.H.)
| | - Hui-Yi Ye
- From the Medical School of Chinese PLA, No. 28 Fuxing Rd, Haidian District, Beijing 100853, China (X.B., S.M.S., H.H.K.); Department of Radiology, First Medical Center, Chinese PLA General Hospital, Beijing, China (X.B., W.X., H.H.K., X.J.Z., H.Y.Y., H.Y.W.); Department of Health Service, Second Medical Center, Chinese PLA General Hospital, Beijing, China (S.M.S.); Department of Medical Statistic, Institute for Hospital Management Research, Chinese PLA General Hospital, Beijing, China (L.L.); Department of Radiology, Huaiyang County People's Hospital, Zhoukou, China (Y.Q.J.); Department of Radiology, Armed Police Corps Hospital of Henan Province, Zhengzhou, China (Q.G.L.G.); Department of Radiology, Zunhua Second Hospital, Zunhua, China (G.C.L.); Department of Radiology, Baoding Qingyuan District People's Hospital, Baoding, China (H.Y.L.); Department of Radiology, Beijing First Hospital of Integrated Chinese and Western Medicine, Beijing, China (L.L.L.); Department of Radiology, Seventh Medical Center, Chinese PLA General Hospital, Beijing, China (S.L.C.); Department of Radiology, The People's Hospital of Xishuangbanna Dai Nationality Autonomous Prefecture, Jinghong, China (Q.R.W.); Department of Radiology, First Affiliated Hospital of Hebei North University, Zhangjiakou, China (P.W.); Department of Pathology, First Medical Center, Chinese PLA General Hospital, Beijing, China (A.T.G.). Department of Urology, First Medical Center, Chinese PLA General Hospital, Beijing, China (Q.B.H.)
| | - Hai-Yi Wang
- From the Medical School of Chinese PLA, No. 28 Fuxing Rd, Haidian District, Beijing 100853, China (X.B., S.M.S., H.H.K.); Department of Radiology, First Medical Center, Chinese PLA General Hospital, Beijing, China (X.B., W.X., H.H.K., X.J.Z., H.Y.Y., H.Y.W.); Department of Health Service, Second Medical Center, Chinese PLA General Hospital, Beijing, China (S.M.S.); Department of Medical Statistic, Institute for Hospital Management Research, Chinese PLA General Hospital, Beijing, China (L.L.); Department of Radiology, Huaiyang County People's Hospital, Zhoukou, China (Y.Q.J.); Department of Radiology, Armed Police Corps Hospital of Henan Province, Zhengzhou, China (Q.G.L.G.); Department of Radiology, Zunhua Second Hospital, Zunhua, China (G.C.L.); Department of Radiology, Baoding Qingyuan District People's Hospital, Baoding, China (H.Y.L.); Department of Radiology, Beijing First Hospital of Integrated Chinese and Western Medicine, Beijing, China (L.L.L.); Department of Radiology, Seventh Medical Center, Chinese PLA General Hospital, Beijing, China (S.L.C.); Department of Radiology, The People's Hospital of Xishuangbanna Dai Nationality Autonomous Prefecture, Jinghong, China (Q.R.W.); Department of Radiology, First Affiliated Hospital of Hebei North University, Zhangjiakou, China (P.W.); Department of Pathology, First Medical Center, Chinese PLA General Hospital, Beijing, China (A.T.G.). Department of Urology, First Medical Center, Chinese PLA General Hospital, Beijing, China (Q.B.H.)
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Affiliation(s)
- Peter L Choyke
- From the Molecular Imaging Program, National Cancer Institute, 10 Center Dr, Building 10, Room B3B69F, Bethesda, MD 20892
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