Potential of quantitative T1 mapping to serve as a novel prognostic predictor of clear cell renal cell carcinoma after nephrectomy

Introduction

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinomas (RCCs), which accounts for about 75% of all RCCs (1,2). At present, surgical resection followed by observation has been a clinical standard treatment for patients with non-metastatic ccRCCs (3). However, up to 60% of high-risk patients with localized ccRCCs will experience recurrence or metastatic disease within 5 years (3,4). Therefore, there is a clinical need for accurate risk stratification of patients with ccRCCs before surgery to enable personalized treatment. The traditional prognostic indicators are tumor grade (5), sarcomatoid transformations, tumor necrosis (6), microvascular infiltration, and the presence of lymph node metastases. Diagnosing these factors needs a biopsy or surgical resection, but they are invasive, time- consuming, and costly. Thus, a non-invasive preoperative imaging method has more potential to guide the clinical decision-making.

Currently, noninvasive imaging methods, including computed tomography (CT) and magnetic resonance imaging (MRI), are employed for early detection of ccRCCs. MRI has an excellent soft-tissue contrast and, unlike CT, does not involve radiation exposure (7). MRI has been routinely used for noninvasive diagnosis (8,9), treatment planning, and treatment response assessment of ccRCCs (10,11). However, conventional MRI can only analyze the characteristics of tumors qualitatively, and the overlapping characteristics of lesions on imaging is another key problem.

The longitudinal (spin-lattice) relaxation time (T1) is a quantifiable property of the tissue in a magnetic field that is related to water content and mobility. T1 mapping is a technique that can provide an absolute value of T1 for quantitative analyses of biological tissue characteristics. In addition, T1 mapping is linearly correlated to the concentration of gadolinium diethylenetriaminepentaacetic acid (GD-DTPA) in both blood and tissue. It could accurately demonstrate the blood supply of ccRCCs. Evidence has shown that T1 mapping may reflect the extracellular expansion and indicate the pathophysiological processes of the lesions (12,13) such as edema, inflammation, and fibrosis (14). Previous studies have reported the usefulness of T1 mapping in grading the ccRCCs (15), distinguishing ccRCCs from fat-poor angiomyolipomas (16), and detecting the severity of renal function and fibrosis (17-19). However, the prognostic value of T1 mapping in patients with ccRCCs remains unclear.

In this study, we aimed to determine whether the quantitative T1 mapping may be used as an imaging biomarker to predict the prognosis of ccRCCs preoperatively. We present this article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-23-1829/rc).

Methods

Patients

The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). This retrospective cohort study obtained approval from the Institutional Review Board of Zhongshan Hospital (No. B2020-214R). Since this is a retrospective review study, the requirement for written informed consent was waived. The data in renal neoplasms of inpatients were collected consecutively and retrospectively from the period between September 2014 and September 2021. All renal incidentalomas discovered by abdominal ultrasonography or CT examinations were confirmed by MRI examinations for further clinical diagnosis. Surgical procedures include laparoscopic or open, radical, or partial nephrectomy. The inclusion criteria were as follows: (I) pathologically confirmed ccRCCs with nephrectomy; (II) MRI performed within 1 month before resection, and the MRI scanning protocol was complete (including T1 mapping before and after contrast enhancement). The exclusion criteria were as follows: (I) patients receiving preoperative neoadjuvant therapy; (II) poor imaging quality with serious artifacts affecting the observation; (III) complete cystic ccRCCs without measurable solid components. The flowchart of this study population is presented in Figure 1.

Figure 1 Flowchart of the study population. ccRCC, clear cell renal cell carcinoma; MRI, magnetic resonance imaging.

Renal MRI

All patients with renal lesions were scanned with the same 1.5T MRI system (Magnetom Area; Siemens Healthineers, Erlangen, Germany) using an 18-channel body array coil. A routine multiparametric renal magnetic resonance (MR) protocol was scanned in the transverse position, including diffusion-weighted imaging (DWI) (b values, 0, 50, and 800 s/mm²), 3-dimensional (3D) in- and out-of-phase T1-weighted interpolated examination imaging (T1WI), T2-weighted fast spin-echo pulse sequence with fat suppression imaging (T2WI), and pre-and post-contrasted dynamic 3D T1-weighted volumetric interpolated examination at corticomedullary phase (CMP, 20–25 s), nephrographic phase (NP, 80–90 s), and excretory phase (EP, 180 s) after injection of 0.1 mmol/kg administration GD-DTPA at a rate of 2 mL/s. The native and enhanced T1 mapping sequences were performed before and at 5 minutes after the administration of GD-DTPA, with a breath-holding interval of 15 seconds, respectively. The parameters were as follows: echo time (TE), 4.38 ms; repetition time (TR), 1.93 ms; slice thickness, 3mm; matrix size 174×288, field of view (FOV) 300 mm × 380 mm; flip angle, 2° and 12°.

Quantitative MR image analysis

Observers (L.Z. with 5 years of experience and Y.D. with 12 years of experience in abdominal MR imaging diagnosis) who were blinded to the pathological diagnosis of tumors independently delineated the regions of interest (ROI) of the lesions. A circular ROI was manually placed in the most avidly enhanced area of the lesions 3 times and an average value was taken for further analysis. All the ROIs were first delineated on the CMP image and then copied to the corresponding unenhanced phase (UP), NP, apparent diffusion coefficient (ADC), and T1 maps. When the tumor was entirely homogeneous, ROIs were outlined around it as large as possible. To minimize the selection bias, we avoided sites adjacent to the renal parenchyma and perinephric fat, as well as heterogeneous compositions (including necrosis, cystic, hemorrhagic, and calcified areas). The reduction rate of T1 relaxation time (T1r) and enhancement rate of corticomedullary phase (CMPr) and nephrographic phase (NPr) were calculated as follows: T1r = (native T1 value − enhanced T1 value)/native T1 value × 100%; CMPr or NPr = (SI_CMP or SI_NP − SI_UP)/SI_UP × 100%, where SI_UP, SI_CMP, and SI_NP were the signal intensity of the lesions on UP, CMP, and NP, respectively.

Follow-up

All patients were followed-up until the end of December 2022. Progression-free survival (PFS) was measured from the date of surgery until the date of confirmed tumor recurrence and metastasis. PFS was censored at the date of death due to other causes or last follow-up at which the patient was alive and recurrence-free (20).

Statistical analysis

Univariate and multivariable Cox proportional hazard regression analyses were conducted to assess risk factors related to the development of recurrence and metastasis. Factors with a P value of 0.05 or less in the univariate regression analysis were all entered into a multivariate model. The forward stepwise method (Forward: LR) variable selection method was used to obtain significant variables for the final model. Subsequently, a comprehensive nomogram based on the findings of multivariable Cox regression was built to predict the 1-, 3-, and 5-year PFS of patients with ccRCC. We used the Schoenfeld residuals to check the proportional hazards assumption in the Cox model. The a priori level of significance was set at 0.05, and the hypothesis tests were 2-sided. The interclass correlation coefficient (ICC) was calculated between 2 observers for T1 mapping parameters. An ICC less than 0.40 was considered indicative of poor interobserver reliability, 0.40–0.59 as fair, 0.60–0.74 as good, and 0.75–1.00 as excellent (21). Kaplan-Meier plots and the log-rank test were used to evaluate the PFS among different independent risk factors. The optimal cutoff value of risk factors was calculated by the receiver operator characteristic (ROC) curve and the Youden index. Statistical analyses were performed with SPSS (version 26.0; IBM Corp., Armonk, NY, USA).

Results

Clinical and pathological characteristics

Table 1 shows the clinical and pathological characteristics of the enrolled patients. Finally, a total of 195 patients with pathologically confirmed ccRCCs were analyzed. Among them, 133 (68%) were male and 62 (32%) were female patients. The mean age was 56.0±12.0 years (range, 26.0–83.0 years). A total of 10 (5%) patients had Fuhrman grade 1 ccRCCs, 151 (77%) had grade 2, 34 (17%) had grade 3, and none (0%) had grade 4. The mean size of the lesions was 4.1±2.1 cm (range, 1.2–10.7 cm).

The median follow-up period was 27.6 months (range, 1–88 months). During the follow-up period, progression of ccRCCs was observed in 22 (11.3%) of 195 patients. Among 22 patients with progression, local recurrence occurred in 2 (9.1%) patients and the time to tumor recurrence was 22 and 53 months, respectively. Distant metastases occurred in 20 patients. Among this group, 13 (59%) patients had lung metastases (median, 14.3 months; range, 1–41 months); 3 (13.6%) patients had bone metastases and the time to tumor recurrence was 11, 33, and 48 months, respectively; 2 (9.1%) patients had retroperitoneal lymph node metastases and the time to tumor recurrence was 43 and 45 months, respectively; 1 (4.5%) patient had metastases in the liver after 30 months follow-up and 1 (4.5%) in the pancreas after 1 month follow-up.

Risk factors of recurrence

Univariate and multivariate Cox regression analyses were applied to identify the preoperative risk factors between the progression group and the non-progression group. At univariate Cox analysis, male gender, older age, larger tumor diameter, irregular shape, tumor necrosis, incomplete capsule, no-defined margin, hypointense T2WI signal intensity, lower ADC value, signal intensity drop-out in out-of-phase T1WI, the enhancement pattern of “wash-in and wash-out” and “delayed enhancement”, the higher post-contrasted T1 relaxation time, and the lower T1r were statistically correlated to tumor recurrence. However, the CMPr and NPr were not statistically different between the progression group and the non-progression group of ccRCCs.

According to multivariate Cox analysis, only the incomplete tumor capsule [P<0.001; hazard ratio (HR), 7.849; 95% confidence interval (CI): 2.614–23.570] and the higher post-contrasted T1 relaxation time (P=0.001; HR, 2.077; 95% CI: 1.350–3.196) were independently associated with ccRCC recurrence. According to multivariate analysis, ADC was not a significant risk factor (Table 2). The prognostic nomograms for 1-, 3-, and 5-year PFS were established by independent risk factors identified in the multivariate Cox analysis. The enhanced T1 relaxation time showed the maximum weight of the points. The age of the patients had a moderate impact on PFS. Capsule completeness showed the minimum weight of the points (Figure 2).

Figure 2 Nomogram for 1-, 3-, and 5-year prediction of PFS for patients with ccRCCs. The enhanced T1 relaxation time showed the maximum weight of the points. Capsule completeness showed a minimum weight of the points. PFS, progression-free survival; ccRCC, clear cell renal cell carcinoma.

Diagnostic performance of T1 relaxation time

The agreement on the T1 relaxation time between the 2 observers was excellent. The ICC of pre-contrasted, post-contrasted, and T1r were 0.821 (95% CI: 0.770–0.862), 0.963 (95% CI: 0.951–0.972), and 0.913 (95% CI: 0.886–0.934), respectively. The mean post-contrasted T1 relaxation time in the recurrence group was significantly higher (273.99±38.55 ms) than those in the non-recurrence group (209.42±61.26 ms), and the T1r was lower (84.15%±4.66% vs. 87.83%±5.29%) (Figure 3).

Figure 3 T1 mapping parameters correlate with tumor progression after nephrectomy. Each box shows the mean values and 25th, 50th, and 75th percentiles. Vertical bars showed the ranges of data that were not outliers. *, the statistical significance between T1 mapping parameters group, P<0.0001. (A) The enhanced T1 in non-recurrence group ccRCCs were lower than the recurrence group. (B) The reduction rate of T1 in the non-recurrence group ccRCCs was higher than those in the recurrence group. ccRCC, clear cell renal cell carcinoma.

PFS for different risk factors

Based on the ROC curve analysis, the optimal cut-off point for post-contrasted T1 relaxation time was 222.73 ms [P<0.001; area under the curve (AUC) =0.814; 95% CI: 0.749–0.879]. Patients with higher post-contrasted T1 relaxation time showed worse PFS than those with lower T1 values (log-rank test, χ²=25.612, P<0.001), and the sensitivity and specificity for predicting tumor progression were 100% and 61.8%, respectively. Worse outcomes were shown in patients with incomplete tumor capsules (log-rank test, χ²=26.475, P<0.001) (Figure 4).

Figure 4 Kaplan-Meier analysis of PFS after nephrectomy in patients with ccRCCs. (A) Patients with higher enhanced T1 relaxation time had worse PFS than patients with lower enhanced T1 relaxation time, P<0.001. (B) Patients with incomplete tumor capsules had worse PFS than those with intact capsules, P<0.001. PFS, progression-free survival; ccRCC, clear cell renal cell carcinoma.

Discussion

Identifying predictors of tumor progression would assist in determining an optimal treatment strategy for patients with ccRCCs. Our study demonstrated that the higher post-contrasted T1 relaxation time and the presence of incomplete capsules of the tumors may predict the worse PFS of ccRCCs after nephrectomy. Figure 5 shows an example of such a case.

Figure 5 A 67-year-old man with a pathologically diagnosed ccRCC in the left kidney, pulmonary metastases were found after a 24-month follow-up. (A) The tumor showed heterogeneous low signal intensity on pre-contrasted T1-weighted imaging.The native T1 map (B) and post-contrasted T1 map (C) of the lesion, with a T1 relaxation time of 2,029.48 and 309.29 ms, respectively. (D) The lesion showed heterogeneous slightly high signal intensity with necrosis, cystic change, and incomplete capsule on T2-weighted imaging (arrows). (E) The lesion demonstrated obvious heterogeneous enhancement on the nephrographic phase image. The arrows indicate an incomplete tumor capsule. ccRCC, clear cell renal cell carcinoma.

The paramagnetic effect of contrast agents (CAs) can reduce the T1 relaxation time, which means the higher the concentration of CAs in the lesions, the lower the post-contrasted T1 relaxation time will be obtained. We observed that the high-risk group of ccRCCs showed a lower concentration of CAs. There are 3 possible reasons for this phenomenon. Firstly, more highly aggressive ccRCCs were observed with more complex cell structures and immature malformed vessels, secondarily decreasing its microvascular density (MVD) (22). Similarly, Yhee et al. (23) and Hemmerlein et al. (24) have shown a significant decrease in MVD from histopathological G1 to G3 RCCs. We speculated that the prolonged post-contrasted T1 relaxation time would be due to the reduction of MVD in the higher aggressive ccRCCs. According to the study of Imao et al. (22), high-grade RCCs enlarge more rapidly, exceeding their vascular network, and neovascularization cannot keep up with tumor cell proliferation. Secondly, most of the ccRCCs display heterogeneity. Although we had done our best to avoid ROIs with the macroscopic areas of tumor degeneration, it may still be difficult to exclude the microscopic necrosis and cystic zones (25-27), which potentially negatively affect the concentration of CAs in aggressive ccRCCs. Thirdly, it was found that tumor progression of ccRCCs was related to the upregulation of extracellular matrix genes and proteins, particularly in higher-grade ccRCCs (28,29). Poorly differentiated ccRCCs were composed of relatively large and irregular tumor cells, resulting in higher cell density and narrow extravascular or interstitial spaces (30), which may partially explain a lower CAs uptake in more highly aggressive ccRCCs. Furthermore, a study by Peng et al. (31) demonstrated that the higher Edmondson-Steiner grade of hepatocellular carcinoma (HCC), the higher the T1 values of the lesions after gadolinium ethoxybenzyl-diethylenetriaminepentaacetic acid (Gd-EOB-DTPA) administration. It was considered that poorly differentiated HCC could result in the loss of part of liver cell functions, leading to a reduced CAs uptake, which may also explain the process in ccRCCs. In addition, our results showed that the CMPr and NPr were not useful in predicting the PFS of ccRCC. This may indicate that T1 mapping can reflect the internal characteristics of tumors, which has advantages over semi-quantitative signal intensity change of the lesions.

We also found that the presence of tumor incomplete capsules was an independent prognostic factor for tumor progression, which was consistent with the results of the previous studies (32). In our cohort, a total of 68 (35%) cases were identified as incomplete capsules, this was in accordance with the results obtained by the previous studies (33,34). The fibrous capsule is considered a result of the expansive growth of the tumor. The presence of a fibrous capsule is a crucial element in determining the tumor’s minimal margin during nephron-sparing surgery. Invasion beyond the renal capsule was a prognostic parameter and was noted to be associated with a poor outcome in patients with renal tumors (35). CcRCCs with infiltration beyond the renal capsule into the peri-renal fat were categorized as T3a stage by the tumor, node, metastasis (TNM) staging system (36). Xi et al. indicated that the absence of pseudocapsule on CT significantly increased the risk of adverse clinical outcomes in RCCs (37). Papalia et al. showed that the characterization of pseudocapsule invasion in renal tumors using MRI could reach a sensitivity of 93.75%, a specificity of 95%, and an AUC of 0.94 (38). A large amount of cohort studies are warranted to further evaluate the prognostic value of fibrosis capsules in ccRCCs.

Previous studies have shown that ADC value derived from functional DWI may effectively help predict the recurrence of RCCs (39,40). However, our results revealed that ADC value was not an independent risk factor for PFS of RCCs. A possible explanation might be the different b values we selected. Furthermore, ADC value can be affected by various factors, including but not limited to MRI scanners, field strengths, and MRI protocols (41).

With the development of novel technologies and artificial intelligence, quantitative imaging has several potential applications in grading renal malignancy. Choi et al. (42) reported that MR radiomics can accurately predict the tumor stage, size, grade, and necrosis (SSIGN) score of ccRCCs, and achieve the highest AUC score at 0.94. Zhao et al. (43) found that a deep learning model based on conventional MRI can predict the histological grade of stage I and II RCCs, and achieved a test accuracy of 0.88. However, there is still a paucity of follow-up information on RCCs in those current published studies.

There are several limitations in our study. Firstly, a sampling bias cannot be excluded; the study included 195 patients with ccRCCs (22 patients with tumor progression and 175 patients without progression). The prognosis of early-stage RCCs is relatively good (44). Secondly, only one 1.5-T MRI scanner was used and the variation of rescanning was not tested, which means that the results of this study may not be generalized to all institutions. Thirdly, only ccRCCs were included in our study; more renal malignant masses may be further investigated, such as papillary and chromophobe subtypes of RCCs. Fourthly, we failed to establish artificial intelligence models, specifically convolutional neural networks (CNN), because of technical limitations. Such research would be the next step in our research program.

Conclusions

Quantitative T1 mapping parameters may be a potential prognostic marker in ccRCCs. The higher enhanced T1 relaxation time could be a predictor of poor prognosis in patients with ccRCCs. In any event, further studies with larger sample sizes are needed to explore the full potential of T1 mapping in ccRCCs.

Acknowledgments

We would like to acknowledge the reviewers for their helpful comments on this paper.

Funding: This study was supported by the National Natural Science Foundation of China (Grant No. 82202285).

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-23-1829/rc

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-23-1829/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). This retrospective cohort study obtained approval from the Institutional Review Board of Zhongshan Hospital (No. B2020-214R). Since this is a retrospective review study, the requirement for written informed consent was waived.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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