RCC is the most common form of kidney cancer, accounting for approximately 90% of all renal malignancies [15]. The three primary RCC subtypes are clear cell, papillary, and chromophobe. It is essential to accurately diagnose and characterize renal tumors for effective treatment planning and prognosis. RCC represents a significant health challenge, with varying biological behaviors and responses to treatment among its subtypes. While traditional imaging modalities, including ultrasound and computed tomography, have been instrumental in detecting renal masses, MRI has proven superior in providing detailed soft-tissue contrast, which is essential for differentiating between RCC subtypes.
MRI has emerged as an important tool for diagnosing and differentiating RCC subtypes due to its superior contrast resolution and multiparametric imaging capabilities [15]. Clinical trials have investigated the characterization and differential diagnosis of renal masses using MRI. Previous studies have focused on the conventional MRI signal features and contrast enhancement patterns to differentiate RCC subtypes and distinguish them from other renal masses. Diffusion-weighted imaging provides additional information about tumor cellularity. RCCs generally exhibit restricted diffusion, appearing hyperintense on high b-value images and hypointense on the corresponding apparent diffusion coefficient maps. Restricted diffusion indicates high cellular density, characteristic of malignant tumors.
Clear cell RCC is the most common subtype, accounting for approximately 70–80% of RCC cases. In MRI, clear cell RCC typically presents as a heterogeneous mass with high signal intensity in T2-weighted images and variable signal intensity in T1-weighted images. Post-contrast sequences often show rapid and intense enhancement due to rich tumor vascularity. Papillary RCCs, which make up 10–15% of RCC cases, usually appear as well-circumscribed masses with low to intermediate signal intensity in T2-weighted images and low signal intensity in T1-weighted images [16]. Unlike clear cell RCCs, papillary RCCs exhibit hypovascularity, resulting in lower and more gradual contrast enhancement [16]. Chromophobe RCCs account for about 5% of RCC cases, and typically present as homogeneous masses with intermediate signal intensity in both T1- and T2-weighted images. The enhancement pattern is less pronounced than that of clear cell RCCs, often demonstrating mild to moderate post-contrast enhancement [17].
Renal oncocytomas are benign epithelial tumors that account for approximately 3–7% of all renal tumors [17]. They are often asymptomatic and may be discovered incidentally during imaging for other conditions. Differentiating oncocytomas from RCCs, particularly chromophobe RCCs, is a significant clinical challenge as both have similar presentations on imaging studies. MRI, with its advanced imaging techniques, provides valuable information for distinguishing these tumors, which is essential for appropriate management.
Oncocytomas typically appear isointense or slightly hypointense relative to the renal cortex in T1-weighted images. The signal intensity is usually homogeneous, although more extensive lesions may show central low signal intensity areas corresponding to a central scar. In T2-weighted images, renal oncocytomas often exhibit a characteristic central stellate scar that appears hyperintense. The peripheral tumor tissue is usually isointense to hyperintense compared to the renal cortex. This central scar is an important feature for differentiating oncocytomas from RCCs, but is not always present. Oncocytomas typically show early and homogeneous enhancement in the arterial phase, followed by rapid washout in the venous phase. The central scar, if present, may enhance later than the peripheral tumor tissue, creating a spoke-wheel pattern. Oncocytomas generally exhibit less restricted diffusion than RCCs, appearing hyperintense on high b-value images and having higher apparent diffusion coefficient values [17].
Renal urothelial carcinoma accounts for approximately 5–10% of all renal tumors, and is the second most common type of renal malignancy after RCC. The primary challenge in diagnosing renal urothelial carcinoma is its differentiation from other renal masses, particularly RCCs, due to overlapping imaging characteristics. MRI, with its superior soft-tissue resolution, provides critical insights into the anatomical and pathological features of renal urothelial carcinomas, facilitating accurate diagnosis and staging [18].
Renal lymphoma usually represents secondary involvement by systemic non-Hodgkin lymphoma and less commonly, Hodgkin lymphoma. Although it accounts for a small fraction of renal tumors, it has significant implications for patient management and prognosis. It is important to differentiate renal lymphoma from other renal masses, such as RCC or metastatic disease. In T2-weighted images, renal lymphoma often exhibits mildly increased signal intensity compared to normal renal parenchyma, and generally homogeneous signal intensity compared to other renal tumors [19].
AMLs are the most common benign renal tumors, and can be associated with tuberous sclerosis complex. These tumors present a diagnostic challenge, particularly the lipid-poor type, as they can resemble malignant RCCs, especially papillary RCCs. Accurate diagnosis of AMLs is essential for appropriate clinical management and to avoid unnecessary surgical interventions. MRI plays a pivotal role in the noninvasive diagnosis of AMLs, providing detailed information about the tissue composition and vascular characteristics of lesions. A key diagnostic feature of the majority of AMLs is the presence of macroscopic fat, resulting in high signal intensity in T1-weighted images. Fat-suppression techniques, such as chemical shift imaging, are particularly useful for confirming the presence of fat, demonstrating signal loss in fat-suppressed sequences. In T2-weighted images, AMLs may appear heterogeneous due to the varying proportions of blood vessels, muscle, and fat.
A subset of AMLs lacks macroscopic fat, which makes the diagnosis more challenging. These lipid-poor AMLs can mimic RCCs in imaging. In T1- and T2-weighted images, lipid-poor AMLs typically exhibit intermediate to low signal intensity. Post-contrast images often reveal early and intense enhancement due to the vascular nature of the tumor, although this can be variable [20].
MRI-PDFF is a novel MRI technique for quantitatively measuring tissue fat content [21]. PDFF allows fat quantification within a tissue, and is an effective and reliable method to reveal liver fat ratios with high sensitivity and specificity. Previous studies have demonstrated that liver fat ratios are highly correlated with liver biopsy results, and effectively indicate the hepatosteatosis grade [22].
In a study of nine transfusion-related iron overload patients, Idilman et al. measured fat ratios in the liver, pancreas, spleen, vertebral bone marrow, and renal cortex, and reported a mean average renal cortex MRI-PDFF of 0.8–1.5% [23]. In our study, the average fat ratio in the normal side renal cortex was 1.15%, with the difference attributable to the difference in patient numbers. Gjela et al. used different measurement techniques to demonstrate that the ratio of kidney cortex fat with MRI-PDFF was 0.4–2% in normal individuals (n = 14) and 0.5–2.3% in obese patients (n = 28), indicating that obesity causes increased renal cortex lipid deposition and fat ratio [24]. In a study of obese patients, the renal cortex fat ratio ranged from 2.9–3.6% depending on the severity of obesity, and the kidney fat ratio decreased as the patients lost weight [25].
Several investigators have demonstrated lipid accumulation in RCCs [26–28]. In particular, clear cell RCCs are histologically characterized by prominent glycogen and lipid storage [29–30].A study of 45 histopathologically diagnosed clear cell RCC patients found that although clear cell RCCs mostly contained intratumoral fat, MRI-PDFF findings were affected by tumor heterogeneity, and the fat content of the tumor decreased as the WHO-ISUP tumor grade increased [27]. A study of diabetic (n = 29) and normal individuals (n = 40) found that the PDFF values of the normal renal cortices were 2.18% and 0.79%, respectively, with a statistically significant difference between the two groups [31]. However, that study did not evaluate other kidney tumor types, and a mean MRI-PDFF value was not reported. Although the fat content of clear cell RCCs is known, previous studies have not investigated the role of fat content for determining tumor subtypes and MRI-PDFF for differential diagnosis.
In our series, we evaluated the diagnostic performance of MRI-PDFF for the preoperative characterization of renal neoplasms and in cases of clear cell RCCs, the prediction of the nuclear tumor grade, as defined by the WHO-ISUP degree. MRI-PDFF was accurate for preoperatively differentiating clear cell RCCs, lipid-poor AMLs, and lipid-rich AMLs from other renal neoplasms, with an overall accuracy of 96.4%. Papillary and chromophobe RCCs and oncocytomas exhibited a lower fat ratio than clear cell RCCs in MRI-PDFF. Histopathologically, these tumors contain less fat than clear cell RCCs. We also detected a lower fat ratio in lymphomas and uroepithelial tumors than in other renal tumor types using MRI-PDFF. Lipid-poor AMLs exhibited a higher fat ratio compared to oncocytomas, lymphomas, uroepithelial tumors, and RCCs, except the clear cell subtype, as measured using MRI-PDFF. In daily radiologic practice, papillary RCC can be mistaken for fat-poor AML due to similar MRI signal behavior, resulting in unnecessary surgeries. One of the key advantages of MRI-PDFF is its capability to distinguish between papillary RCC and fat-poor AML. In addition, the fat ratio decreased as the WHO-ISUP grade increased in clear cell RCC patients, consistent with previous studies [27].
Our results suggest that, while MRI-PDFF may not be the primary imaging technique for investigating renal tumors, it holds promise as an efficient method for renal oncologic imaging. The presurgical diagnosis of clear cell RCCs, lipid-poor AMLs, and lipid-rich AMLs using MRI-PDFF could potentially prevent unnecessary radical nephrectomies, thereby reducing the incidence of diagnostic surgical explorations for renal lesions and enhancing patient care. Furthermore, larger studies could enable the preoperative differentiation of lipid-poor AMLs and papillary RCCs.
There were some limitations to our study. First, our sample included only a small number of lymphomas and lipid-poor AMLs. It is known, however, that clear cell RCCs greatly outnumber other RCC subtypes, lymphomas, uroepithelial tumors, and benign renal tumors. In addition, we did not assess intraobserver reliability. A significant limitation of this study was the lack of a direct comparison between the diagnostic performances of multiparametric MRI and MRI-PDFF for evaluating renal tumors. Such a comparison could clarify the role of MRI-PDFF relative to multiparametric MRI in diagnosing and characterizing renal tumors.
In conclusion, MRI-PDFF is an effective diagnostic tool for evaluating and differentiating renal tumors. It demonstrated high accuracy for the preoperative differentiation of clear cell RCCs and other renal tumors, offering high sensitivity and specificity.