Novel Imaging Methods for Renal Mass Characterization: A Collaborative Review

被引:73
作者
Roussel, Eduard [1 ]
Capitanio, Umberto [2 ,3 ]
Kutikov, Alexander [4 ]
Oosterwijk, Egbert [5 ]
Pedrosa, Ivan [6 ,7 ,8 ]
Rowe, Steven P. [9 ,10 ,11 ]
Gorin, Michael A. [12 ,13 ,14 ]
机构
[1] Univ Hosp Leuven, Dept Urol, Leuven, Belgium
[2] Univ Vita Salute, San Raffaele Sci Inst, Dept Urol, Milan, Italy
[3] IRCCS San Raffaele Sci Inst, Urol Res Inst, Div Expt Oncol, URI, Milan, Italy
[4] Temple Univ Hlth Syst, Fox Chase Canc Ctr, Dept Surg, Div Urol, Philadelphia, PA USA
[5] Radboud Univ Nijmegen, Radboud Inst Mol Life Sci RIMLS, Med Ctr, Dept Urol, Nijmegen, Netherlands
[6] Univ Texas Southwestern Med Ctr Dallas, Dept Radiol, Dallas, TX 75390 USA
[7] Univ Texas Southwestern Med Ctr Dallas, Adv Imaging Res Ctr, Dallas, TX 75390 USA
[8] Univ Texas Southwestern Med Ctr Dallas, Dept Urol, Dallas, TX 75390 USA
[9] Johns Hopkins Univ, Sch Med, Russell H Morgan Dept Radiol & Radiol Sci, Baltimore, MD USA
[10] Johns Hopkins Univ, Sch Med, James Buchanan Brady Urol Inst, Baltimore, MD USA
[11] Johns Hopkins Univ, Sch Med, Dept Urol, Baltimore, MD 21205 USA
[12] Urol Associates, Cumberland, MD USA
[13] UPMC Western Maryland, Cumberland, MD USA
[14] Univ Pittsburgh, Sch Med, Dept Urol, Pittsburgh, PA USA
关键词
Renal cell carcinoma; Kidney cancer; Multiparametric magnetic resonance imaging; Girentuximab; Radiomics; Virtual biopsy; Tc-99m-sestamibi; PET; SPECT; Machine learning; Artificial intelligence; EMISSION TOMOGRAPHY/COMPUTED TOMOGRAPHY; CELL CARCINOMA IMPLICATIONS; FAT-POOR ANGIOMYOLIPOMA; CARBONIC-ANHYDRASE IX; CLEAR-CELL; DIAGNOSTIC-ACCURACY; ARTIFICIAL-INTELLIGENCE; RADIOMICS FEATURES; DIFFERENTIATION; CT;
D O I
10.1016/j.eururo.2022.01.040
中图分类号
R5 [内科学]; R69 [泌尿科学(泌尿生殖系疾病)];
学科分类号
1002 ; 100201 ;
摘要
Context: The incidental detection of localized renal masses has been rising steadily, but a significant proportion of these tumors are benign or indolent and, in most cases, do not require treatment. At the present time, a majority of patients with an incidentally detected renal tumor undergo treatment for the presumption of cancer, leading to a significant number of unnecessary surgical interventions that can result in complications including loss of renal function. Thus, there exists a clinical need for improved tools to aid in the pretreatment characterization of renal tumors to inform patient management. Objective: To systematically review the evidence on noninvasive, imaging-based tools for solid renal mass characterization. Evidence acquisition: The MEDLINE database was systematically searched for relevant studies on novel imaging techniques and interpretative tools for the characterization of solid renal masses, published in the past 10 yr. Evidence synthesis: Over the past decade, several novel imaging tools have offered promise for the improved characterization of indeterminate renal masses. Technologies of particular note include multiparametric magnetic resonance imaging of the kidney, molecular imaging with targeted radiopharmaceutical agents, and use of radiomics as well as artificial intelligence to enhance the interpretation of imaging studies. Among these, Tc-99m-sestamibi single photon emission computed tomography/computed tomography (CT) for the identification of benign renal oncocytomas and hybrid oncocytic chromophobe tumors, and positron emission tomography/CT imaging with radiolabeled girentuximab for the identification of clear cell renal cell carcinoma, are likely to be closest to implementation in clinical practice. Conclusions: A number of novel imaging tools stand poised to aid in the noninvasive characterization of indeterminate renal masses. In the future, these tools may aid in patient management by providing a comprehensive virtual biopsy, complete with information on tumor histology, underlying molecular abnormalities, and ultimately disease prognosis. Patient summary: Not all renal tumors require treatment, as a significant proportion are either benign or have limited metastatic potential. Several innovative imaging tools have shown promise for their ability to improve the characterization of renal tumors and provide guidance in terms of patient management. (C) 2022 European Association of Urology. Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:476 / 488
页数:13
相关论文
共 120 条
  • [41] MicroRNAs Possibly Involved in the Development of Bone Metastasis in Clear-Cell Renal Cell Carcinoma
    Kinget, Lisa
    Roussel, Eduard
    Lambrechts, Diether
    Boeckx, Bram
    Vanginderhuysen, Loic
    Albersen, Maarten
    Rodriguez-Antona, Cristina
    Grana-Castro, Osvaldo
    Inglada-Perez, Lucia
    Verbiest, Annelies
    Zucman-Rossi, Jessica
    Couchy, Gabrielle
    Caruso, Stefano
    Laenen, Annouschka
    Baldewijns, Marcella
    Beuselinck, Benoit
    [J]. CANCERS, 2021, 13 (07)
  • [42] Artificial Intelligence in Renal Mass Characterization: A Systematic Review of Methodologic Items Related to Modeling, Performance Evaluation, Clinical Utility, and Transparency
    Kocak, Burak
    Kaya, Ozlem Korkmaz
    Erdim, Cagri
    Kus, Ece Ates
    Kilickesmez, Ozgur
    [J]. AMERICAN JOURNAL OF ROENTGENOLOGY, 2020, 215 (05) : 1113 - 1122
  • [43] Radiomics of Renal Masses: Systematic Review of Reproducibility and Validation Strategies
    Kocak, Burak
    Durmaz, Emine Sebnem
    Erdim, Cagri
    Ates, Ece
    Kaya, Ozlem Korkmaz
    Kilickesmez, Ozgur
    [J]. AMERICAN JOURNAL OF ROENTGENOLOGY, 2020, 214 (01) : 129 - 136
  • [44] Radiogenomics in Clear Cell Renal Cell Carcinoma: Machine Learning-Based High-Dimensional Quantitative CT Texture Analysis in Predicting PBRM1 Mutation Status
    Kocak, Burak
    Durmaz, Emine Sebnem
    Ates, Ece
    Ulusan, Melis Baykara
    [J]. AMERICAN JOURNAL OF ROENTGENOLOGY, 2019, 212 (03) : W55 - W63
  • [45] Kotecha RR, 2019, NAT REV CLIN ONCOL, V16, P621, DOI 10.1038/s41571-019-0209-1
  • [46] Arterial Spin-labeling MR Imaging of Renal Masses: Correlation with Histopathologic Findings
    Lanzman, Rotem S.
    Robson, Phil M.
    Sun, Maryellen R.
    Patel, Amish D.
    Mentore, Kimiknu
    Wagner, Andrew A.
    Genega, Elizabeth M.
    Rofsky, Neil M.
    Alsop, David C.
    Pedrosa, Ivan
    [J]. RADIOLOGY, 2012, 265 (03) : 799 - 808
  • [47] Past, Present, and Future: Development of Theranostic Agents Targeting Carbonic Anhydrase IX
    Lau, Joseph
    Lin, Kuo-Shyan
    Benard, Francois
    [J]. THERANOSTICS, 2017, 7 (17): : 4322 - 4339
  • [48] Differentiation of fat-poor angiomyolipoma from clear cell renal cell carcinoma in contrast-enhanced MDCT images using quantitative feature classification
    Lee, Han Sang
    Hong, Helen
    Jung, Dae Chul
    Park, Seunghyun
    Kim, Junmo
    [J]. MEDICAL PHYSICS, 2017, 44 (07) : 3604 - 3614
  • [49] Deep feature classification of angiomyolipoma without visible fat and renal cell carcinoma in abdominal contrast-enhanced CT images with texture image patches and hand-crafted feature concatenation
    Lee, Hansang
    Hong, Helen
    Kim, Junmo
    Jung, Dae Chul
    [J]. MEDICAL PHYSICS, 2018, 45 (04) : 1550 - 1561
  • [50] Kidney cancer management 3.0: can artificial intelligence make us better?
    Lee, Matthew
    Wei, Shuanzeng
    Anaokar, Jordan
    Uzzo, Robert
    Kutikov, Alexander
    [J]. CURRENT OPINION IN UROLOGY, 2021, 31 (04) : 409 - 415