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Article

The Incidence of Oncocytoma and Angiomyolipoma in Patients Undergoing Nephron-Sparing Surgery for Small Renal Masses

1
Department of Urology, “Carol Davila” University of Medicine and Pharmacy, 4192910 Bucharest, Romania
2
Center of Uronephrology and Kidney Transplantation, Fundeni Clinical Institute, 022328 Bucharest, Romania
3
Department of Nephrology, Urology, Immunology and Immunology of Transplant, Dermatology, Allergology, Faculty of Medicine, “Carol Davila” University of Medicine and Pharmacy, 050474 Bucharest, Romania
4
Department of Surgery, “Carol Davila” University of Medicine and Pharmacy, 050474 Bucharest, Romania
5
Department of Visceral Surgery, Center of Excellence in Translational Medicine, Fundeni Clinical Institute, 022328 Bucharest, Romania
6
Department of Visceral Surgery, Center of Digestive Diseases and Liver Transplantation, Fundeni Clinical Institute, 022328 Bucharest, Romania
7
Department of Visceral Surgery, “St. Pantelimon” Clinical Hospital, 021659 Bucharest, Romania
*
Author to whom correspondence should be addressed.
J. Mind Med. Sci. 2025, 12(2), 38; https://doi.org/10.3390/jmms12020038
Submission received: 5 April 2025 / Revised: 5 June 2025 / Accepted: 8 July 2025 / Published: 16 July 2025

Abstract

Background: Oncocytoma and angiomyolipoma (AML) are benign renal tumors that may mimic malignant lesions on imaging. With the increasing use of partial nephrectomy (PN) for renal masses, accurate preoperative characterization of these lesions is essential. This study highlights the role of partial nephrectomy as a valuable diagnostic tool in situations where imaging is inconclusive or raises concern for malignancy without definitive confirmation. In the absence of a reliable preoperative diagnosis, partial nephrectomy provides direct histologic verification with minimal perioperative morbidity. Moreover, it offers curative potential when malignancy is present. By achieving both diagnostic certainty and renal preservation, this approach is well-suited for clinical scenarios in which imaging ambiguity might otherwise result in overtreatment through radical surgery or undertreatment Material and methods: in this retrospective study, we reviewed our 5-year experience (2019–2024), 188 partial nephrectomies—including bilateral procedures and operations on solitary kidneys—using robotic and open approaches. All of these 30 tumors were solid renal masses with indeterminate imaging features or suspicious characteristics suggestive of malignancy, further underscoring the limitations of current preoperative diagnostic modalities. Results: Histopathological evaluation confirmed benign renal tumors in 30 cases, with oncocytoma diagnosed in 18 cases (16 robotic, 2 open) and AML in 12 cases (9 robotic, 3 open). Conclusions: Even when imaging raises suspicion of malignancy or remains inconclusive, many small renal masses are ultimately confirmed as benign upon histopathological examination. This study underscores the diagnostic uncertainty associated with small renal tumors and highlights the value of partial nephrectomy as a decisive diagnostic intervention. In situations where non-invasive modalities fail to provide definitive answers, partial nephrectomy offers tissue confirmation with minimal morbidity. Furthermore, when malignancy is present, this approach ensures appropriate oncologic management while preserving renal function. Our findings support the integration of this strategy into routine clinical practice, particularly when diagnostic clarity is essential for guiding safe and effective treatment.

1. Introduction

Benign renal tumors, such as oncocytoma and angiomyolipoma, pose significant diagnostic challenges because their radiologic features can closely mimic those of renal cell carcinoma (RCC). Oncocytomas are benign epithelial masses, while AMLs are mesenchymal tumors composed of adipose tissue, smooth muscle, and blood vessels [1,2,3].
Benign tumors represent approximately 15% of all renal masses encountered in clinical practice. In most cases, computed tomography (CT) remains the primary imaging modality employed to differentiate between benign and malignant lesions. When imaging characteristics strongly favor a benign diagnosis, a conservative management strategy—such as active surveillance—is often adopted. Although there is no universally accepted follow-up protocol, clinical evaluations combined with CT imaging are commonly performed at 3, 6, and 12 months, and subsequently on an annual basis [4,5].
Given the persistent diagnostic ambiguity, identifying preoperative clinical predictors of benign histology may reduce the risk of overtreatment and associated morbidity [6]. In situations where imaging remains inconclusive, percutaneous renal biopsy can provide critical diagnostic clarification [5,7,8].
Definitive treatment for benign renal tumors is typically reserved for symptomatic cases—most often presenting with flank pain or hematuria—or for tumors exceeding 7 cm in diameter. Available therapeutic approaches include surgical resection, selective embolization, and image-guided ablative techniques such as radiofrequency ablation or cryoablation [5]. When imaging cannot definitively rule out malignancy, histologic confirmation through biopsy or excision remains warranted.
The frequency of benign pathology among surgically resected renal masses has been reported to range from 7% to 33%, depending on population characteristics and study design. Consistently, smaller renal tumors are more likely to exhibit benign histologic features [9,10,11,12,13,14,15,16].
Recent advances in minimally invasive surgery, particularly robotic-assisted techniques, have significantly enhanced the feasibility of nephron-sparing procedures, which are crucial for preserving renal function, especially in patients with solitary kidneys or bilateral renal involvement [17,18,19]. Despite progress in imaging, even experienced radiologists face challenges due to the inherent limitations of CT and MRI, including variability in imaging protocols, pseudo-enhancement artifacts in small or central lesions, and the lack of standardized diagnostic criteria [2,20]. As a result, distinguishing between benign and malignant renal tumors preoperatively often remains uncertain.
In this context, all partial nephrectomies performed in our study were indicated by either inconclusive imaging findings or a high suspicion of malignancy. Given this diagnostic uncertainty and the imperative of renal function preservation, surgical intervention was deemed appropriate. Partial nephrectomy not only enabled adequate oncological control when necessary but also allowed for a definitive histopathological diagnosis in cases that ultimately proved to be benign.
The primary aim of this study is to demonstrate that partial nephrectomy can serve as a reliable diagnostic tool in cases of renal tumors with inconclusive or suspicious imaging, particularly when non-invasive methods fail to provide certainty. Beyond its diagnostic value, partial nephrectomy also offers therapeutic benefits, ensuring oncologic control when malignancy is confirmed. A secondary objective is to highlight that this approach is associated with minimal intraoperative risks and low morbidity, while maintaining excellent long-term postoperative outcomes.
Here, we present our 5-year experience with 188 partial nephrectomies and focus on the incidence, management, and outcomes of benign renal tumors.

2. Materials and Methods

After receiving the approval of the Ethics Committee of SANADOR Hospital, no. 121/21.12.2024, a retrospective study was conducted on 188 partial nephrectomies performed between 2019 and 2024. The series included 148 robotic-assisted and 40 open procedures. Only renal tumors with imaging or clinical features suggestive of malignancy or presenting diagnostic uncertainty were included in the analysis; cases with a definitive preoperative diagnosis of benign pathology (e.g., classic angiomyolipoma with visible fat or prior histological confirmation) were excluded. The indication for partial nephrectomy was established based on clinical and imaging criteria suggestive of malignancy and R.E.N.A.L nephrometry score. Although in some situations the risk of malignancy was high (e.g., intermediate/high R.E.N.A.L. score, tumor size > 3 cm), the decision to avoid radical nephrectomy was justified by the need to preserve renal function in all cases if feasible, especially in cases with solitary kidney, comorbidities, and young patients. A multidisciplinary team composed of a radiologist, urologist, oncologist, and anesthesiologist (tumor board) reviewed each case and determined the appropriate treatment approach. The choice of surgical approach (robotic vs. open) was determined by patient comorbidities, prior abdominal surgeries, tumor location, and the preferences of both the surgeon and the patient. Open surgery was performed via a dorsal flank incision (with an anterior transperitoneal approach when indicated), with tumor removal achieved by enucleation, resection, or wedge resection and arterial clamping in all cases. Robotic partial nephrectomy was performed transperitoneally using the DaVinci Xi system, with arterial clamping used in every case; tumor resection was performed by standard resection or enucleation. Preoperative data regarding age, associated comorbidities, renal function, perioperative outcomes, and histopathological findings were collected from all cases and analyzed using SPSS 22.0 software; a p-value < 0.05 was considered statistically significant.

3. Results

Patients included those undergoing unilateral, bilateral, or solitary-kidney surgeries. Preoperative imaging (CT, MRI, or ultrasound) was used for surgical planning, although a definitive radiologic diagnosis of benign lesions was rarely established preoperatively. Final diagnoses were determined by histopathological evaluation. In this series, benign tumors were identified in 30 cases: oncocytoma in 18 patients (16 robotic, 2 open) and AML in 12 patients (9 robotic, 3 open).
Data regarding baseline demographics of the patients are summarized in Table 1.
Intraoperative, perioperative, and postoperative outcomes are summarized in Table 2.
Among the 188 partial nephrectomies performed for solid renal masses, benign tumors were confirmed in 30 cases (16%). Oncocytomas accounted for 18 cases (10.1% of all procedures) and AMLs for 12 cases (6.9%). The robotic approach was utilized in 83.3% of benign cases, with 16 of 18 oncocytomas and 9 of 12 AMLs managed robotically; the open approach was used in the remaining cases.
Overall, benign tumors were more frequent in females (70%) than in males (30%). The left kidney was involved in 56.7% of cases. Oncocytoma was more common in males (75% of oncocytomas), whereas AML was predominantly found in females (72.7% of AMLs).
Perioperative outcomes demonstrated that robotic-assisted procedures were associated with lower blood loss and shorter hospital stays. Specifically, for oncocytomas, robotic cases had an average blood loss of approximately 90.9 mL compared with 150.5 mL in open cases, and a hospital stay of 4.88 days compared with 6.0 days for open cases. Notably, in the robotic oncocytoma group, two trocar site hematomas were observed, while in the open oncocytoma group, a wound infection was recorded. For AML, robotic procedures averaged 77.9 mL blood loss and 4.67 days of hospitalization, while open procedures showed 287.8 mL blood loss and a 5.0-hospital stay; additionally, the open AML group experienced a perirenal hematoma that necessitated blood transfusions. The warm ischemia time ranged between 19 and 35 min, without a direct comparison between the robotic and open cohorts. No transfusions or complications occurred in robotic cases, whereas two AML open cases required transfusions, and one experienced a complication necessitating embolization.

4. Discussion

Benign renal tumors accounted for 16% of all partial nephrectomies in our series, encompassing 18 oncocytomas and 12 AML. While these lesions were predominantly managed using a robotic approach—mirroring the rising popularity of robotic-assisted partial nephrectomy for small renal masses—preoperative imaging remained limited in reliably distinguishing benign from malignant lesions [21,22]. Consequently, partial nephrectomy serves both diagnostic and therapeutic purposes, ensuring definitive pathological confirmation while preserving renal function when malignancy cannot be excluded.
We compared the two groups of benign tumors because their clinical behavior and surgical response can differ significantly, particularly in the context of diagnostic imaging limitations. Classic AMLs typically present with intratumoral fat and low attenuation on CT (–10 to –100 HU), which facilitates diagnosis. However, fat-poor AMLs lack visible fat and may appear as solid, homogeneous, or heterogeneous masses, mimicking malignancy. These tumors are further classified as hyperattenuating or isoattenuating based on unenhanced CT values [23].
Hyperattenuating AMLs (>45 HU) often show early contrast enhancement with washout and appear hypointense on T2-weighted MRI. Isoattenuating AMLs (−10 to +45 HU), on the other hand, may exhibit gradual enhancement and demonstrate signal drop on opposed-phase MRI due to microscopic fat. Despite these distinctions, overlap with RCC imaging features persists, particularly with papillary RCC. Therefore, percutaneous biopsy may be needed for accurate diagnosis [23,24].
Further complicating the diagnostic landscape are AML subtypes such as AMLEC (angiomyolipoma with epithelial cysts), which mimic Bosniak IV cystic lesions and demonstrate enhancing solid components with T2 hypointensity and occasional signal drop. Epithelioid AMLs (EAMLs), which carry malignant potential, typically appear large, heterogeneous, and may invade renal veins or the IVC. T2 hypointensity is a common MRI feature [23,24,25].
In patients with tuberous sclerosis complex (TSC), AMLs occur frequently, are often multiple, bilateral, and fat-poor, with higher hemorrhagic risk and rapid growth. Hemorrhagic AMLs add to the diagnostic difficulty as internal bleeding can obscure fat and increase attenuation. Indications for treatment include lesions larger than 4 cm or aneurysms over 5 mm. Embolization is the first-line treatment in active bleeding but is associated with a higher recurrence rate than surgery [23,24].
Large AMLs may also mimic retroperitoneal liposarcomas. Differentiation is aided by features such as the “claw sign”—indicating renal parenchyma enveloping the lesion—and identification of renal feeding vessels [23].
The overlap in imaging characteristics, especially in retroperitoneal or perirenal soft tissue masses, often prevents definitive preoperative diagnosis. In ambiguous cases, MRI can improve lesion characterization but lacks absolute specificity. Thus, percutaneous biopsy remains a valuable adjunct in selected cases when imaging is inconclusive and differentiation between benign and malignant pathology critically impacts clinical management [23,24].
Oncocytomas, by contrast, are more frequently confused with RCC due to their radiologic appearance. The analysis of these differences between benign subtypes and malignancies provides essential insights into perioperative planning and highlights the utility of partial nephrectomy not only as a treatment but also as a diagnostic tool. This dual role is particularly relevant in small renal masses with uncertain imaging profiles [23].
The limitations of CT and MRI in evaluating renal masses contribute significantly to this diagnostic challenge. CT imaging, despite its ability to assess attenuation and enhancement patterns, is often unable to reliably differentiate benign lesions—such as oncocytomas and minimal fat angiomyolipomas—from malignant tumors. Factors such as variability in scanning protocols, the phenomenon of pseudo-enhancement (particularly in small or centrally located lesions), and concerns over radiation exposure further limit CT’s diagnostic accuracy. Similarly, while MRI offers enhanced soft tissue characterization through techniques like subtraction imaging and diffusion-weighted imaging, it is not free from shortcomings. Technical variability and a lack of standardized protocols across institutions hinder their ability to definitively distinguish benign from malignant renal tumors [25,26]. These inherent limitations in cross-sectional imaging underscore the necessity of surgical intervention, not only for treatment but also for obtaining a definitive histopathologic diagnosis when imaging findings remain ambiguous.
Notably, approximately 10–15% of resected renal tumors prove benign on final pathology [27,28], which reinforces the merit of parenchyma-sparing strategies, especially in uncertain cases. In our cohort, there was an overall female majority (70%), a slightly higher incidence of left-sided tumors, and a tendency for oncocytomas to occur more often in men, whereas AMLs were more common in women. Importantly, the mild changes in serum creatinine and estimated glomerular filtration rate (eGFR) observed at six months post-surgery support the notion that partial nephrectomy confers both curative and diagnostic value without significantly compromising renal function. It seems that AMLs larger than 4 cm or symptomatic masses typically warrant intervention due to the risk of life-threatening hemorrhage [29]. However, smaller, asymptomatic AMLs are amenable to conservative management, including active surveillance (AS) when feasible [30,31,32,33].
Nonetheless, differentiating small benign renal tumors from malignant ones using imaging alone continues to pose significant challenges, largely due to the limited sensitivity and specificity of currently available radiologic techniques. To enhance diagnostic accuracy before surgery, several minimally invasive imaging tools are under evaluation. Among these, contrast-enhanced ultrasound (CEUS) has emerged as a valuable adjunct to standard imaging in characterizing renal masses [4,5,7]. Similarly, 99mTc-sestamibi SPECT/CT is being studied for its potential to better define indeterminate lesions [8]. Although preliminary results are encouraging, broader clinical validation is necessary before these modalities can be routinely implemented.
The diagnostic challenge of fat-poor AML has led to increasing interest in machine-learning and radiomics approaches [34,35,36,37,38], as demonstrated by Feng et al. (2018), who reported excellent accuracy (93.9%) in differentiating these lesions from renal cell carcinoma (RCC) via quantitative texture analysis [39]. Similarly, Coy et al. (2019) showcased the potential of deep-learning algorithms (Google TensorFlow™ Inception) to distinguish clear cell RCC from oncocytoma on multiphasic CT, achieving sensitivity surpassing 85% and reinforcing artificial intelligence as a future adjunct to standard imaging [38].
Furthermore, active surveillance—particularly for small renal masses (SRMs) suspicious for clinical T1a RCC—has emerged as a valuable option [37,38,39], avoiding overtreatment in select patients (Lee et al., 2018) [40]. Prospective data, such as from the Delayed Intervention and Surveillance for Small Renal Masses (DISSRM) Registry, confirm low metastatic rates and high cancer-specific survival, indicating that for older patients or those with significant comorbidities, vigilant monitoring can preserve renal function and quality of life while awaiting definitive signs of disease progression [41,42,43].
Taken together, these findings highlight a multifaceted shift in how benign and indeterminate renal lesions are approached. Nephron-sparing surgery, including robotic partial nephrectomy, remains the gold standard for suspicious tumors, balancing oncologic control with organ preservation [44,45]. However, the concomitant rise in artificial intelligence and the broader acceptance of active surveillance suggest a future in which overtreatment is minimized, imaging accuracy is enhanced, and individualized patient management is increasingly refined [36,37,38].
However, our study also has certain limitations. One of the primary limitations of our study is the heterogeneity of imaging investigations. The imaging data were sourced from multiple healthcare units rather than being standardized within the same institution where the surgeries were performed. This variability in imaging protocols and quality across centers may have introduced inconsistencies in data interpretation and measurement, potentially affecting the overall comparability of the findings.
Another significant limitation concerns the imbalance in the patient groups. The number of patients undergoing open surgery versus robotic surgery was unequal, which could introduce bias into our analysis. This discrepancy limits the generalizability of our results and may reduce the statistical power needed to detect significant differences between the two surgical approaches [46,47,48].
Future research should aim to standardize imaging protocols by centralizing the imaging investigations or adopting uniform guidelines across all participating centers. Additionally, ensuring balanced patient cohorts for different surgical modalities would enhance the reliability of comparative outcomes and improve the validity of the study’s conclusions.

5. Conclusions

Even when imaging raises suspicion of malignancy or remains inconclusive, many small renal masses are ultimately confirmed as benign upon histopathological examination. This study underscores the diagnostic uncertainty associated with small renal tumors and highlights the value of partial nephrectomy as a decisive diagnostic intervention. In situations where non-invasive modalities fail to provide definitive answers, partial nephrectomy offers tissue confirmation with minimal morbidity. Furthermore, when malignancy is present, this approach ensures appropriate oncologic management while preserving renal function. Our findings support the integration of this strategy into routine clinical practice, particularly when diagnostic clarity is essential for guiding safe and effective treatment.

Author Contributions

Conceptualization: S.I.; Methodology: I.B.; Validation: N.B.; software: C.B.; Formal Analysis: C.G.; writting original draft: S.I. and I.B.; writting—review and editing: N.B.; data resources: I.S.; project administration: I.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of SANADOR Hospital, no. 121/21.12.2024.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Data are available from the corresponding author on reasonable request.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Birnbacher, L.; Braunagel, M.; Willner, M.; Marschner, M.; De Marco, F.; Viermetz, M.; Auweter, S.; Notohamiprodjo, S.; Hellbach, K.; Notohamiprodjo, M.; et al. Quantitative differentiation of minimal-fat angiomyolipomas from renal cell carcinomas using grating-based X-ray phase-contrast computed tomography: An ex vivo study. PLoS ONE 2023, 18, e0279323. [Google Scholar] [CrossRef] [PubMed]
  2. Allgood, E.; Raman, S.S. Image Interpretation: Practical Triage of Benign from Malignant Renal Masses. Radiol. Clin. N. Am. 2020, 58, 875–884. [Google Scholar] [CrossRef] [PubMed]
  3. Kay, F.U.; Pedrosa, I. Imaging of Solid Renal Masses. Urol. Clin. N. Am. 2018, 45, 311–330. [Google Scholar] [CrossRef] [PubMed]
  4. Ljunberg, B.; Albiges, L.; Bedke, J.; Bex, A.; Capitanio, U.; Giles, R.; Hora, M.; Klatte, T.; Lam, T.; Marconi, L.; et al. Guidelines on Renal Cell Carcinoma. Available online: https://uroweb.org/guidelines/renal-cell-carcinoma (accessed on 21 January 2025).
  5. Lounová, V.; Študent, V., Jr.; Purová, D.; Hartmann, I.; Vidlář, A.; Študent, V. Frequency of benign tumors after partial nephrectomy and the association between malignant tumor findings and preoperative clinical parameters. BMC Urol. 2024, 24, 175. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  6. Bauman, T.M.; Potretzke, A.M.; Wright, A.J.; Knight, B.A.; Vetter, J.M.; Figenshau, R.S. Partial Nephrectomy for Presumed Renal-Cell Carcinoma: Incidence, Predictors, and Perioperative Outcomes of Benign Lesions. J. Endourol. 2017, 31, 412–417. [Google Scholar] [CrossRef] [PubMed]
  7. Li, N.; Hu, Z.; Liu, Y.; Ding, J.; Han, P.; Jing, X.; Kan, Y. Dynamic contrast-enhanced ultrasound characteristics of renal tumors: VueBox™ quantitative analysis. Clin. Hemorheol. Microcirc. 2023, 85, 341–354. [Google Scholar] [CrossRef] [PubMed]
  8. Basile, G.; Fallara, G.; Verri, P.; Uleri, A.; Chiti, A.; Gianolli, L.; Pepe, G.; Tedde, A.; Algaba, F.; Territo, A.; et al. The role of 99mTc-Sestamibi single-photon Emission Computed Tomography/Computed Tomography in the diagnostic pathway for renal masses: A systematic review and Meta-analysis. Eur. Urol. 2024, 85, 63–71. [Google Scholar] [CrossRef] [PubMed]
  9. Richard, P.O.; Jewett, M.A.; Bhatt, J.R.; Kachura, J.R.; Evans, A.J.; Zlotta, A.R.; Finelli, A. Renal tumor biopsy for small renal masses: A single-center 13-year experience. Eur. Urol. Apr. 2015, 68, 1007–1013. [Google Scholar] [CrossRef] [PubMed]
  10. Halverson, S.J.; Kunju, L.P.; Bhalla, R.; Gadzinski, A.J.; Alderman, M.; Miller, D.C.; Wolf, J.S. Accuracy of determining small renal mass management with risk stratified biopsies: Confirmation by final pathology. J. Urol. 2013, 189, 441–446. [Google Scholar] [CrossRef] [PubMed]
  11. Fujii, Y.; Komai, Y.; Saito, K.; Iimura, Y.; Yonese, J.; Kawakami, S.; Fukui, I. Incidence of benign pathologic lesions at partial nephrectomy for presumed RCC renal masses: Japanese dual-center experience with 176 consecutive patients. Urol. Sep. 2008, 72, 598–602. [Google Scholar] [CrossRef] [PubMed]
  12. Jeon, H.G.; Lee, S.R.; Kim, K.H.; Oh, Y.T.; Cho, N.H.; Rha, K.H.; Yang, S.C.; Han, W.K. Benign lesions after partial nephrectomy for presumed renal cell carcinoma in masses 4 cm or less: Prevalence and predictors in korean patients. Urology 2010, 76, 574–579. [Google Scholar] [CrossRef] [PubMed]
  13. Kutikov, A.; Fossett, L.K.; Ramchandani, P.; Tomaszewski, J.E.; Siegelman, E.S.; Banner, M.P.; Van Arsdalen, K.N.; Wein, A.J.; Malkowicz, S.B. Incidence of benign pathologic findings at partial nephrectomy for solitary renal mass presumed to be renal cell carcinoma on preoperative imaging. Urology 2006, 68, 737–740. [Google Scholar] [CrossRef] [PubMed]
  14. Lindkvist Pedersen, C.; Winck-Flyvholm, L.; Dahl, C.; Azawi, N.H. High rate of benign histology in radiologically suspect renal lesions. Dan. Med. J. Oct. 2014, 61, A4932. [Google Scholar]
  15. McKiernan, J.; Yossepowitch, O.; Kattan, M.W.; Simmons, R.; Motzer, R.J.; Reuter, V.E.; Russo, P. Partial nephrectomy for renal cortical tumors: Pathologic findings and impact on outcome. Urology 2002, 60, 1003–1009. [Google Scholar] [CrossRef] [PubMed]
  16. Marszalek, M.; Ponholzer, A.; Brossner, C.; Wachter, J.; Maier, U.; Madersbacher, S. Elective open nephron-sparing surgery for renal masses: Single-center experience with 129 consecutive patients. Urol. Jul. 2004, 64, 38–42. [Google Scholar] [CrossRef] [PubMed]
  17. Capitanio, U.; Bensalah, K.; Bex, A.; Boorjian, S.A.; Bray, F.; Coleman, J.; Gore, J.L.; Sun, M.; Wood, C.; Russo, P. Epidemiology of Renal Cell Carcinoma. Eur. Urol. 2019, 75, 74–84. [Google Scholar] [CrossRef] [PubMed]
  18. Siegel, R.L.; Miller, K.D.; Jemal, A. Cancer statistics, 2018. CA Cancer J. Clin. 2018, 68, 7–30. [Google Scholar] [CrossRef] [PubMed]
  19. Nguyen, K.A.; Brito, J.; Hsiang, W.; Nolte, A.; Syed, J.S.; Suarez-Sarmiento, A.; Leapman, M.S.; Such, B. National trends and economic impact of surgical treatment for benign kidney tumors. Urol. Oncol. 2019, 37, 183-e9. [Google Scholar] [CrossRef] [PubMed]
  20. Kim, J.; Lee, J.S.; Jo, Y.; Han, W.K. Superiority of magnetic resonance imaging in small renal mass diagnosis where image reports mismatches between computed tomography and magnetic resonance imaging. Investig. Clin. Urol. 2023, 64, 148–153. [Google Scholar] [CrossRef] [PubMed]
  21. Chen, M.C.; Chang, Y.H.; Sheng, T.W.; Huang, L.K.; Kan, H.C.; Liu, C.Y.; Lin, P.H.; Yu, K.J.; Chuang, C.K.; Pang, S.T.; et al. Predicting Bleeding Related Events in Robotic-Assisted Partial Nephrectomy for Angiomyolipoma: Simplifying Risk Assessment with Tumor Diameter and Depth, A Retrospective Study. Ther. Clin. Risk Manag. 2024, 20, 883–892. [Google Scholar] [CrossRef] [PubMed]
  22. Sidoti Abate, M.A.; Menold, H.S.; Neuberger, M.; Kirchner, M.; Haney, C.M.; Nuhn, P.; Westhoff, N.; Honeck, P.; Michel, M.S.; Kriegmair, M.C.; et al. Quality-of-life outcomes of the ROBOtic-assisted versus Conventional Open Partial nephrectomy (ROBOCOP) II trial. BJU Int. 2024, 134, 434–441. [Google Scholar] [CrossRef] [PubMed]
  23. Lienert, A.R.; Nicol, D. Renal angiomyolipoma. BJU Int. 2012, 25, 7. [Google Scholar] [CrossRef] [PubMed]
  24. Jinzaki, M.; Silverman, S.G.; Akita, H.; Nagashima, Y.; Mikami, S.; Oya, M. Renal angiomyolipoma: A radiological classification and update on recent developments in diagnosis and management. Abdom Imaging 2014, 39, 588–604. [Google Scholar] [CrossRef] [PubMed]
  25. Snyder, M.E.; Bach, A.; Kattan, M.W.; Raj, G.V.; Reuter, V.E.; Russo, P. Incidence of benign lesions for clinically localized renal masses smaller than 7 cm in radiological diameter: Influence of sex. J. Urol. 2006, 176, 2391–2395. [Google Scholar] [CrossRef] [PubMed]
  26. Liu, J.; Homewood, D.; Rajarubendra, N.; Rashid, P.; Bolton, D.; Lawrentschuk, N. Common incidental urological lesions on computed tomography images: What to do with renal and adrenal computed tomography incidentalomas in a primary care setting. Aust. J. Gen. Pract. 2024, 53 (Suppl. 11), S47–S52. [Google Scholar] [CrossRef] [PubMed]
  27. Joshi, B.M.; Desai, P.; Dwivedi, G.; Ranjan, S.; Kumar, A. Living Donor Renal Transplant After Ex Vivo Partial Nephrectomy for Incidentally Detected Small Renal Mass: A Case Series. Exp. Clin. Transpl. 2025, 23, 116–119. [Google Scholar]
  28. Schachter, L.R.; Cookson, M.S.; Chang, S.S.; Smith, J.A.; Dietrich, M.S.; Jayaram, G.; Herrell, S.D. Second prize: Frequency of benign renal cortical tumors and histologic subtypes based on size in a contemporary series: What to tell our patients. J. Endourol. 2007, 21, 819–823. [Google Scholar] [CrossRef] [PubMed]
  29. Nicolau, C.; Antunes, N.; Paño, B.; Sebastia, C. Imaging Characterization of Renal Masses. Medicina 2021, 57, 51. [Google Scholar] [CrossRef] [PubMed]
  30. Flum, A.S.; Hamoui, N.; Said, M.A.; Yang, X.J.; Casalino, D.D.; McGuire, B.B.; Perry, K.T.; Nadler, R.B. Update on the Diagnosis and Management of Renal Angiomyolipoma. J. Urol. 2016, 195 Pt 1, 834–846. [Google Scholar] [CrossRef] [PubMed]
  31. Romero-Fernández, S.; García-Ramos, V.; García, V.; Ceballos, M.L. Postembolization syndrome in a patient with a giant renal angiomyolipoma: A case report. Radiol. Case Rep. 2024, 19, 6269–6273. [Google Scholar] [CrossRef] [PubMed]
  32. Mach, M.; Maciejewski, K.; Ostrowski, T.; Maciąg, R.; Sajdek, M.; Gałązka, Z. Endovascular Treatment of a Bilateral, Ruptured Angiomyolipoma in a Patient With Tuberous Sclerosis Complex. Cureus 2024, 16, e66200. [Google Scholar] [CrossRef] [PubMed]
  33. Zeid, M.; Sayedin, H.; Nabi, N.; Abdelrahman, M.; Jacob, P.T.; Alhadi, B.; Giri, S. Active Surveillance for Renal Angiomyolipoma Less Than 4 Centimeters: A Systematic Review of Cohort Studies. Cureus 2022, 14, e22678. [Google Scholar] [CrossRef] [PubMed]
  34. Troncoso, P.; Rojas, P.A.; Saavedra, Á. Masas renales pequeñas: Predictores de malignidad en una serie de 10 años [Small renal masses. Analysis of 152 cases]. Rev. Med. Chil. 2019, 147, 703–708. [Google Scholar] [CrossRef] [PubMed]
  35. Kan, H.C.; Lin, P.H.; Shao, I.H.; Cheng, S.C.; Fan, T.Y.; Chang, Y.H.; Huang, L.K.; Chu, Y.C.; Yu, K.J.; Chuang, C.K.; et al. Using deep learning to differentiate among histology renal tumor types in computed tomography scans. BMC Med. Imaging 2025, 25, 66. [Google Scholar] [CrossRef] [PubMed]
  36. Han, J.H.; Kim, B.W.; Kim, T.M.; Ko, J.Y.; Choi, S.J.; Kang, M.; Kim, S.Y.; Cho, J.Y.; Ku, J.H.; Kwak, C.; et al. Fully automated segmentation and classification of renal tumors on CT scans via machine learning. BMC Cancer 2025, 25, 173. [Google Scholar] [CrossRef] [PubMed]
  37. Uhlig, A.; Uhlig, J.; Leha, A.; Biggemann, L.; Bachanek, S.; Stöcklem, M.; Reichert, M.; Lotz, J.; Zeuschner, P.; Maßmann, A. Radiomics and machine learning for renal tumor subtype assessment using multiphase computed tomography in a multicenter setting. Eur. Radiol. 2024, 34, 6254–6263. [Google Scholar] [CrossRef] [PubMed]
  38. Coy, H.; Hsieh, K.; Wu, W.; Nagarajan, M.B.; Young, J.R.; Douek, M.L.; Brown, M.S.; Scalzo, F.; Raman, S.S. Deep learning and radiomics: The utility of Google TensorFlow™ Inception in classifying clear cell renal cell carcinoma and oncocytoma on multiphasic CT. Abdom. Radiol. 2019, 44, 2009–2020. [Google Scholar] [CrossRef] [PubMed]
  39. Feng, Z.; Rong, P.; Cao, P.; Zhou, Q.; Zhu, W.; Yan, Z.; Liu, Q.; Wang, W. Machine learning-based quantitative texture analysis of CT images of small renal masses: Differentiation of angiomyolipoma without visible fat from renal cell carcinoma. Eur. Radiol. 2018, 28, 1625–1633. [Google Scholar] [CrossRef] [PubMed]
  40. Lee, H.; Hong, H.; Kim, J.; Jung, D.C. 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. Med. Phys. 2018, 45, 1550–1561. [Google Scholar] [CrossRef] [PubMed]
  41. Ray, S.; Cheaib, J.G.; Pierorazio, P.M. Active Surveillance for Small Renal Masses. Rev. Urol. 2020, 22, 9–16. [Google Scholar] [PubMed]
  42. Pallauf, M.; Rezaee, M.; Elias, R.; Wlajnitz, T.; Fletcher, S.A.; Cheaib, J.; Alkhatib, K.; Chang, P.; Wagner, A.A.; McKiernan, J.M.; et al. Tumour size is associated with growth rates of >0.5 cm/year and delayed intervention in small renal masses in patients on active surveillance. BJU Int. 2025, 135, 860–868. [Google Scholar] [CrossRef] [PubMed]
  43. Alam, R.; Yerrapragada, A.; Wlajnitz, T.; Watts, E.; Pallauf, M.; Enikeev, D.; Chang, P.; Wagner, A.A.; McKiernan, J.M.; Pierorazio, P.M.; et al. Evaluation of Growth Rates for Small Renal Masses in Elderly Patients Undergoing Active Surveillance. Eur. Urol. Open Sci. 2023, 50, 78–84. [Google Scholar] [CrossRef] [PubMed]
  44. Metcalf, M.R.; Cheaib, J.G.; Biles, M.J.; Patel, H.D.; Peña, V.N.; Chang, P.; Wagner, A.A.; McKiernan, J.M.; Pierorazio, P.M. Outcomes of Active Surveillance for Young Patients with Small Renal Masses: Prospective Data from the DISSRM Registry. J. Urol. 2021, 205, 1286–1293. [Google Scholar] [CrossRef] [PubMed]
  45. Guo, P.; Wang, H.; Wang, Z.; Xu, T.; Li, J.; Xu, Y.; Ding, D.; Li, C.; Teng, L.; Chen, H.; et al. Robot-assisted partial nephrectomy and robot-assisted radical prostatectomy using the Chinese surgical systems KangDuo-SR-2000 and EDGE MP1000 versus the Da Vinci Xi system: A prospective, single-center, non-randomized clinical trial. World J. Urol. 2025, 43, 205. [Google Scholar] [CrossRef] [PubMed]
  46. Banno, T.; Kobari, Y.; Fukuda, H.; Yoshida, K.; Hirai, T.; Omoto, K.; Iizuka, J.; Shimizu, T.; Ishida, H.; Takagi, T. Comparing surgical outcomes between robot-assisted laparoscopic and open partial nephrectomy for allograft kidney tumors: A retrospective, single-center study. BMC Surg. 2025, 25, 103. [Google Scholar] [CrossRef]
  47. Thiravit, S.; Teerasamit, W.; Thiravit, P. The different faces of renal angiomyolipomas on radiologic imaging: A pictorial review. Br. J. Radiol. 2018, 91, 20170533. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  48. Furrer, M.A.; Spycher, S.C.J.; Büttiker, S.M.; Gross, T.; Bosshard, P.; Thalmann, G.N.; Schneider, M.P.; Roth, B. Comparison of the diagnostic performance of contrast-enhanced Ultrasound with that of contrast-enhanced computed tomography and contrast-enhanced magnetic resonance imaging in the evaluation of renal masses: A systematic review and Meta-analysis. Eur. Urol. Oncol. 2020, 3, 464–473. [Google Scholar] [CrossRef] [PubMed]
Table 1. Baseline demographics.
Table 1. Baseline demographics.
All Patients (n = 30)Oncocytoma (n = 18)AML (n = 12)p Value
Surgery type (%)
Open
Robotic

5 (16.7%)
25 (83.3%)

2 (11.1%)
16 (88.9%)

3 (25%)
9 (75%)
0.32
Age (mean, years)58.6 ± 11.164.4 ± 8.549.92 ± 8.78<0.001
Gender (%)
Male
Female

9 (30%)
21 (70%)

8 (44.4%)
10 (55.6%)

1 (8.3%)
11 (91.7%)
0.02
Nephrectomy side
Left
Right


17 (56.7%)
13 (43.3%)


11 (61.1%)
7 (38.9%)


6 (50%)
6 (50%)
0.55
Baseline serum creatinine (mean, mg/dL)0.80 ± 0.100.86 ± 0.080.71 ± 0.110.002
Serum creatinine at last follow-up 0.83 ± 0.120.87 ± 0.100.77 ± 0.110.01
eGFR at baseline (mean, mL/min/1.73 m2)91.32 ± 10.3585.42 ± 14.50100.17 ± 8.320.003
eGFR at last follow-up (mean, mL/min/1.73 m2)87.33 ± 17.2082.93 ± 18.2593.92 ± 10.050.06
R.E.N.A.L. n (%)
Low (4–6)
Intermediate (7–9)

17 (56.7%)
13 (43.3%)

10 (55.6%)
8 (44.4%)

7 (58.3%)
5 (41.7%)
0.88
HTA13 (43.3%)11 (61.1%)2 (16.7%)0.01
Diabetes3 (10%)3 (16.7%)0 (0%)0.14
Obesity5 (16.7%)3 (16.7%)2 (16.7%)1
Table 2. Tumor characteristics and perioperative outcomes.
Table 2. Tumor characteristics and perioperative outcomes.
VariableOncocytoma (n = 18)AML (n = 12)
Surgery TypeOpen (n = 2)Robotic (n = 16)p ValueOpen (n = 3)Robotic (n = 9)p Value
Tumor Dimension (cm, mean)3.17 ± 0.412.82 ± 0.230.073.30 ± 0.782.55 ± 0.430.06
RENAL ScoreLow/IntermediateLow/Intermediate Low/Intermediate/High Low/Intermediate
Charlson comorbidity index5.5 ± 1.04.2 ± 1.00.103.5 ± 0.82.56 ± 0.80.10
Hospital Stay (days, mean)6 ± 25 ± 10.235 ± 24.7 ± 10.72
Blood Loss (mL, median)150.5 (50–250)90.88 (50–200)0.01287.75 (50–550)77.89 (50–150)<0.001
Transfusions0 (0%)0 (0%)-2 (66.7%)0 (0%)0.01
Complications1 (50%)2 (12.5%)0.191 (33.3%)0 (0%)0.08
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Ianiotescu, S.; Gingu, C.; Balescu, I.; Bacalbasa, N.; Balalau, C.; Sinescu, I. The Incidence of Oncocytoma and Angiomyolipoma in Patients Undergoing Nephron-Sparing Surgery for Small Renal Masses. J. Mind Med. Sci. 2025, 12, 38. https://doi.org/10.3390/jmms12020038

AMA Style

Ianiotescu S, Gingu C, Balescu I, Bacalbasa N, Balalau C, Sinescu I. The Incidence of Oncocytoma and Angiomyolipoma in Patients Undergoing Nephron-Sparing Surgery for Small Renal Masses. Journal of Mind and Medical Sciences. 2025; 12(2):38. https://doi.org/10.3390/jmms12020038

Chicago/Turabian Style

Ianiotescu, Stelian, Constantin Gingu, Irina Balescu, Nicolae Bacalbasa, Cristian Balalau, and Ioanel Sinescu. 2025. "The Incidence of Oncocytoma and Angiomyolipoma in Patients Undergoing Nephron-Sparing Surgery for Small Renal Masses" Journal of Mind and Medical Sciences 12, no. 2: 38. https://doi.org/10.3390/jmms12020038

APA Style

Ianiotescu, S., Gingu, C., Balescu, I., Bacalbasa, N., Balalau, C., & Sinescu, I. (2025). The Incidence of Oncocytoma and Angiomyolipoma in Patients Undergoing Nephron-Sparing Surgery for Small Renal Masses. Journal of Mind and Medical Sciences, 12(2), 38. https://doi.org/10.3390/jmms12020038

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