Introduction

Urolithiasis is a prominent concern in urology, ranking third in terms of illness prevalence. The global incidence rate is 1%-20%, but in Asia it varies from 5 to 19.1%1,2,3,4. In recent years, the incidence rate has shown a continuous upward trend1,5.

With the progress of medical technology, lithotripsy is becoming less intrusive6. For renal calculus larger than 2.0 cm, the EAU guidelines recommend percutaneous nephrolithotomy (PCNL) as the primary option3. In recent years, the application of retrograde intrarenal surgery (RIRS) has increased significantly5, RIRS is not only the first choice for treating intrarenal stones < 2.0 cm, but it can also be employed when PCNL is not available3,7. However, with the popularization of minimally invasive surgeries and the expansion of the indications of RIRS, the problem of postoperative residual stone also follows closely, which can cause recurrence of calculus, urinary infection, urinary tract obstruction, and renal function impairment8,9.

The stone-free rate (SFR) after surgery is an indicator to evaluate the effect of stone clearance after surgery, which is usually determined by CT and KUB7. Stone size, location and number, stone hardness, stone type, patient’s gender, BMI, and the anatomy of the urinary tract, skin-to-stone distance, renal function, etc. are all influencing factors of the stone clearance rate10,11,12,13,14,15,16.

Patients with kidney stones usually accompany with hydronephrosis. After the renal parenchyma of the patient is compressed, the thickness of the cortex will become thinner. Some studies have found that the thickness of the renal parenchyma is related to the SFR and also possesses a certain predictive value17,18,19, but due to individual differences, especially for patients with hydronephrosis, it cannot reflect the relative thickness of renal parenchyma. Hence, this research introduces a new index, the ratio of renal parenchymal volume to renal volume (RPRV) of the affected kidney, with the goal of investigating its link with SFR after RIRS and its prediction role for SFR after RIRS in stones with a diameter of 2–4 cm.

Methods

Patients and study design

This study retrospectively investigated 119 urinary calculus patients who underwent holmium laser lithotripsy through RIRS in the Urology Department of the Fifth Affiliated Hospital of Guangzhou Medical University from March to September 2023. According to the postoperative stone clearance situation, all the patients were divided into a stone-free group and residual stone group, and the age, gender, BMI, stone information, preoperative data of the two groups were recorded. All patients gave informed consent to this study. This study was approved by the institutional committee review (GYWY-L2024-101), and it complies with the ethical principles of “ < Declaration of Helsinki > ”.

Inclusion criteria

  • Patients’ age ranges from 18 to 60 years old;

  • Diagnosed as urinary calculi, with single or cumulative diameter of stones being 20–40 mm, distributed in the upper ureteral segment or within the kidney;

  • Preoperative serum creatinine value is < 144 μmol/L.

Exclusion criteria

  • Patients with missing data, such as the lack of imaging data;

  • Patients with lower ureteral stones;

  • Patients with abnormal kidney anatomy, combined with renal insufficiency, chronic kidney disease;

  • Patients with preoperative uncontrolled urinary tract infection.

Surgical method

Patients with positive preoperative urine culture received anti-infective treatment. During the operation, patients were given general anesthesia and placed in lithotomy position; A 8.0/9.8Fr ureteral rigid endoscope (Richard–Wolf) was used to expand the ureter of the affected side to the renal pelvis and leave a zebra guide wire, after the rigid endoscope was withdrawn, a 12/14F sheath (Flexor Ureteral Access Sheath) was inserted along the guide wire, and a flexible endoscope (URF-V, Olympus) was put into the renal pelvis along the sheath. When stones were found it was shattered by holmium laser (Lumenis PowerSuite60w), and parameters were set as follow: 1–2 J, 10–30 Hz, 200–365 μm. Stone fragments were removed as much as possible, and the stone fragments was discharged by itself. A 6F ureteral stent was placed postoperatively and removed after 4 weeks. All surgeries were performed by the same urologist, who has over ten years of surgical experience and performs approximately 300 RIRS procedures annually. 4–12 weeks after the lithotripsy, KUB or CT was used to evaluate the stone clearance rate. No residual stones means stones were absented or a single asymptomatic stone less than 2 mm was found.

Study variable

The data such as patient’s gender, age, BMI, stone size, location, and density were collected. The renal volume and renal parenchymal volume of the affected kidneys were retrospectively measured using the Canon 640 image processing and analysis software after 3D modeling with CT plain scan. (Toshiba’s third-generation super high-end 640-slice praseodymium gold CT—Aquilion ONE VISION/GE 64-row 128-layer high-end spiral CT). After loading the 5.0 mm thin slice image of the kidney scan, use the volume calc to outline the contour of the kidney at the appropriate CT value. When the boundary is discontinuous, close the contour of the kidney through the extension line. Similarly, after excluding the renal pelvis, fat, blood vessels, and other non-renal parenchymal tissues, outline the inner contour of the kidney to finally obtain the values of the renal parenchymal volume and the renal volume (see appendix Fig.  1.1). The ratio of the two is the RPRV, and the equation is as follows.

$$RPRV = \frac{{\text{Renal Parenchymal Volume }}}{{\text{Renal Volume}}}$$

Statistical analyses

Patients were grouped into the stone-free group and the residual stone group based on the postoperative stone clearance. Data were analyzed by SPSS 25.0. The Shapiro–Wilk test assessed variable normality. Normal variables are reported as mean ± standard deviation (M ± SD) and compared with t-tests, while skewed ones are described by medians and analyzed using Mann–Whitney U tests. Categorical data, summarized as percentages, were tested with chi-square or Fisher’s exact tests, considering P < 0.05 (two-tailed) as significant. According to the stone size, it was divided into 2–2.9 cm and 3–4 cm groups, and univariate and multivariate analyses were done with logistic regression to determine the risk factors of residual stones. The ROC curve was applied to assess the predictive efficiency. The AUC between 0.7 and 0.9 indicated good value, and > 0.9 indicated high accuracy.

Results

Baseline characteristics

This research included a total of 119 participants, among whom 86 were men (72.27%). The median age was 45 (38, 52) years old, the BMI was 24.8 ± 3.29 kg/m2, the median renal parenchymal volume was 146.5 (125.73, 172) cm3, the median renal volume was 194.55 (166.15, 225.01) cm3, and the median RPRV was 0.76 (0.71, 0.81); the stone median size was 2.9 (2.3, 2.5) cm; the average density was 730.85 ± 227.27 HU, and stones of multiple locations accounted for 77.31%. According to the postoperative stone clearance, it was divided into the stone-free group (n = 85, 71.43%) and the residual stone group, refer to Table 1 for details. Gender, age, BMI, kidney volumes, renal parenchymal volume and stone characteristics were similar between the two group. (P > 0.05). However, the RPRV values between the two groups showed a statistically significant difference (P = 0.002).

Table 1 The characteristics of patients and the features of stones based on the postoperative stone clearance.
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The relationship between different factors and SFR in different stone size subgroups

It was divided into two groups according to the stone size: 2–2.9 cm and 3–4 cm (Table 2).

Table 2 The relationship between various risk factors and SFR based on different stone sizes.
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There were 62 patients in the 2–2.9 cm group (52.10%), among which the stone-free subgroup accounted for 72.58% (n = 45), and the rest is the residual stone group. There was no statistical difference in gender, age, BMI, renal parenchymal volume, renal volume, stone size, stone density, and stone location between the two groups (P > 0.05); while the RPRV and the SFR were statistically significant (P = 0.008).

There were 57 patients in the 3–4 cm group. The stone-free subgroup accounted for 70.18% (n = 57). There was no statistical difference in gender, age, BMI, renal parenchymal volume, renal volume, RPRV, stone density, and stone location between the two groups (P > 0.05); but the stone size had statistical significance in the difference of the SFR (P = 0.049).

Multivariate regression analysis between influencing factors and residual stone risk

Patients’ gender, stone location, stone size, stone density, and RPRV were considered, and logistic regression analysis was performed on different stone sized groups to establish a multivariate regression model (Table 3). In the 2–2.9 cm group, RPRV was statistically significant for risk of residual stones (OR 0.847, 95% CI 0.761–0.942, P = 0.002), indicating that the risk of stone residue decreased with increasing RPRV. However, in the 3–4 cm stone group, the stone size has no statistical significance with the risk of postoperative residual stones (P > 0.05).

Table 3 Multivariate regression analysis.
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ROC analysis for RPRV

To explore whether the RPRV affects the SFR after RIRS, an ROC curve was plotted (Table 4, Figs. 1, 2 and 3), and the optimal cutoff value was defined. Among the overall sample and the 2–2.9 cm stone group, the RPRV could predict the SFR after RIRS (P < 0.05). The AUC of the overall sample was 0.678, the optimal cut-off value was 0.689, the sensitivity was 95.3%, and the specificity was 41.2%. The optimal cut-off value of 2–2.9 cm group was 0.6887 (AUC 0.769, sensitivity 97.8%, specificity 58.8%). However RPRV was not a reliable predictor of postoperative SFR in the 3–4 cm group (P > 0.05).

Table 4 The ROC curve analysis results of RPRV and SFR.
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Fig. 1
figure 1

ROC curve for the overall population.

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Fig. 2
figure 2

ROC curve for the 2–2.9 cm group.

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Fig. 3
figure 3

ROC curve for the 3–4 cm group.

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The ROC curves are shown in the figures below.

Discussion

In this study, among 119 patients, 85 are in the stone-free group (71.43%), showing the impressive effect of RIRS in clearing stones. The proportion of men is relatively large, with a median age of 45 years, conforming to the characteristics of nephrolithiasis4,20. There is no statistical difference in gender, age, BMI, and other aspects between the two groups, meaning the samples are comparable. The renal parenchymal thickness and RPRV in the stone-free group are higher, and the latter has a statistical difference, suggesting a correlation between RPRV and SFR after RIRS. RIRS in this study are not limited to 2 cm, and the SFR has not been affected due to the stone size, which can also be seen from multivariate regression analysis between stone size and SFR (Table 3, P > 0.05). Both in univariate analysis (P = 0.008) and multivariate logistic regression analysis (OR 0.847, 95% CI 0.761–0.942, P = 0.002), RPRV has statistical significance with SFR. The larger the RPRV, the lower the risk of residual stones and the higher the SFR. While in the 3–4 cm group, there is no statistical significance between RPRV and SFR, and the stone burden is a factor affecting SFR (P = 0.049), although this difference disappears after adjusting for confounding factors. We suspect that the stone size may interfere with the influence of RPRV, resulting in neither of the two risk factors has obvious statistical significance. The predictive impact is more significant in the 2–2.9 cm group (AUC: 0.769; cut-off value 0.6887; sensitivity: 97.8%; specificity: 58.8%; P = 0.001), according to this study’s evaluation of the predictive performance of RPRV. That might be because stones between 2–3 cm have a higher propensity to move and obstruct the ureter, which would induce hydronephrosis and affect the kidney function, which impacts the excretion of minerals in urine and the development of stones21,22. Consequently, stone clearance following surgery is impacted. The point was also confirmed by Courtney Lee et al. In a retrospective analysis, the SFR of several renal functions was compared among 27,299 individuals who underwent ESWL. It was discovered that individuals with a creatinine level between 2.0–2.9 mg/dL had a lower SFR than those with a level less than 2.0mg/dL23.

The renal volume and the renal parenchymal volume are correlated with age, gender, height, weight, BMI, body surface area and total body water24,25,26,27,28. The renal volume and glomerular filtration rate decrease with age26, and some studies have reported that in healthy adults under the age of 65, the renal parenchymal volume is affected by body size and gender, but not by age or race27. There are few studies on the relationship between the renal parenchymal volume and the SFR. Sedat Taştemur et al. performed a retrospective analysis of 238 patients who underwent RIRS and performed multivariate logistic regression analysis. They found that the renal parenchymal volume in the stone-free success group was thicker, and the difference was statistically significant (P < 0.001). In the ROC analysis, a renal parenchymal volume < 141.3 cm3 was an independent risk factor for the success of the operation (OR 5.923; 95% Cl 2.886–19.263; P = 0.008). The authors suggest that a larger renal parenchyma, indicating more nephrons, may improve diuresis and facilitate the passage of urinary stones29. However, our study found that renal volume and renal parenchymal volume were not related to the SFR, while RPRV < 0.6887 was a risk factor for residual stones after RIRS, for every 0.01 unit decrease in the RPRV, the risk of stone residue after RIRS surgery increases by 15.3%. This may be because the index introduced in this paper can not only offset the errors caused by individual differences, but also make the difference in cortical thinning more significant when there is hydronephrosis, which can better reflect the condition of hydronephrosis (this is also the reason why RPRV has high sensitivity). This index is novel and has not been discussed in any other studies. It not only has high sensitivity, but also is convenient, fast, inexpensive, painless, and non-invasive, and thus has strong potential for clinical application, especially for patients with hydronephrosis. It has unlimited potential in guiding clinical decisions. For example, for patients with a lower RPRV, more aggressive measures may need to be taken to promote the excretion of stone fragments, such as performing external physical vibration lithecbole (EPVL) after RIRS or even change treatments option to PCNL.

There are some limitations of this study. This study has a relatively small sample size and is restricted to one center. Due to limitations in data availability, variables such as stone composition and immediate stone-free rate were not assessed in this study. Future research should aim to include these variables to provide a more comprehensive evaluation. However, we are confident that this study will offer insightful information to the clinic. If possible, multi-center large-sample prospective studies are needed, a clinical prediction model can also be created to further improve the predictive function of RPRV.

Conclusion

The RPRV has a relatively good predictive effect on the SFR after RIRS, especially in stone size ranging 2–2.9 cm. This study introduces a novel, accurate, and non-invasive prognostic indicator for clinical practice, which has certain guiding value for clinical decision-making, along with starting targeted medical treatments for high-risk groups.