Quantification of real-time maximal renal perfusion using dynamic renal imaging

Introduction

As a highly vascularized organ, the kidneys exhibit dynamic changes in blood flow perfusion to adapt to the metabolic demands of the body, demonstrating the high adaptability and reserve capacity of the kidneys (1-9). Quantitative assessment of the real-time maximum renal blood perfusion (MAX-RP) is of significant clinical value for predicting whether the kidneys can completely compensate, selecting surgical approaches for kidney operations, and choosing kidney transplant donors. Currently, the clinical methods for evaluating renal hemodynamics are limited. Computed tomography angiography (CTA) and magnetic resonance angiography (MRA) are restricted due to the risk of nephrotoxicity from contrast agents; although quantitative magnetic resonance imaging (MRI) perfusion has potential, it is easily affected by respiratory movements and is costly, with the reproducibility of results needing improvement (10). Color Doppler renal resistance index (RRI) is commonly used, but it reflects blood flow resistance rather than perfusion volume itself, and cannot assess blood flow reserve (11,12). Intra-renal resistive index variability (IRRIV) can evaluate renal blood flow reserve, but its results are easily influenced by factors such as patient body type, and it cannot precisely quantify the maximum perfusion volume (13-15).

Renal dynamic imaging (RDI) can dynamically record the entire process of renal blood flow perfusion. The morphological changes of its time-activity curve (TAC), especially the peak, contain important hemodynamic information and are closely related to the renal reserve function and compensatory capacity. Sengar et al. found that qualitative assessment of renal blood perfusion based on RDI is crucial for predicting renal prognosis and guiding treatment strategies, especially for patients with normal glomerular filtration rate (GFR) but requiring long-term bladder management, highlighting its key role in prognosis judgment (16). For a long time, due to the varying activity of the injected radioactive drugs, the peak value of TAC fluctuated greatly, making it difficult to be directly used for quantitative analysis (17), which limited the clinical application of the peak value of renal blood flow TAC. This study innovatively proposed a calculation model for the renal blood perfusion peak ratio (RBPPR), which eliminated the interference of individual differences in the activity of radioactive drug injection through the ratio method, aiming to provide new technical ideas and quantitative indicators for the quantitative assessment of MAX-RP and the prediction of renal reserve function. We present this article in accordance with the STARD reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-2026-0704/rc).

Methods

Participants

Patient data from those who underwent RDI examinations from August 2020 to June 2025 were retrospectively collected. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This study was approved by the Ethics Committee of The First Affiliated Hospital of Anhui University of Science and Technology (approval No. 2024-KY-BY013), and the requirement for individual consent for this retrospective analysis was waived.

The inclusion criteria were as follows: age ≥18 years, complete clinical data.

The exclusion criteria were as follows: cases with failed “bolus” injection, including: renal perfusion curve curves showing “saw tooth” or “bimodal” patterns indicative of extravasation (18).

Grouping

The grouping was defined based on the 30% limit of the renal graph peak difference rate (RGPDR, that is, the ratio of the peak difference between the renal graphs on both sides of the same patient to the higher peak). The participants were divided into the control group and the experimental groups (patients whose renal function on one side has declined due to obstructive diseases and whose contralateral kidney is in a compensatory state, it contains 2 subgroups). According to the minimum standard (MS) for normal values of each kidney GFR (ekGFR) estimated GFR (eGFR) of the same body surface, age, and gender integral kidney in the single-photon emission computed tomography (SPECT) database, the experimental groups were divided into a complete compensation group and an incomplete compensation group.

Examination methods

The radiochemical purity of the labeled ^99mTc-DTPA (technetium-labeled stannous pyridylacetic acid for injection) was >95%. The SPECT/CT was a Siemens Symbia-T6 device (Siemens, Erlangen, Germany) equipped with a low-energy high-resolution parallel-hole collimator, and the post-processing SyngoMI VA60C software was provided by Siemens. According to the renal dynamic operation procedure of nuclear medicine standards, the examination was conducted as follows: 30 minutes before the examination, the patient drank 500 mL of water, emptied the bladder, and recorded their height and weight. Image acquisition: The baseline count of the imaging agent in the syringe was collected (collection time: 30 s, collection distance: 30 cm, matrix: 128×128, energy peak: 140 keV). The patient was in a supine position. The collection distance was kept as close as possible. A “bullet-like” injection of ^99mTc-DTPA (185–370 MBq) was administered via the elbow vein. Immediately, SPECT collection was performed: the blood flow perfusion phase (2 seconds/frame × 30 frames) and the functional phase (1 minute/frame × 25 frames). After the collection was completed, the radioactivity count of the empty syringe was measured again (collection time: 30 s, collection distance: 30 cm, matrix: 128×128, energy peak: 140 keV).

Image analysis

Post-processing was performed using professional nuclear medicine image processing software. The region of interest (ROI) technique was applied to delineate the bilateral kidneys and the abdominal aorta region (the delineation range of the bilateral kidneys’ ROI was the edge of the renal parenchyma, and the ROI of the abdominal aorta was at the level of the renal artery opening of the abdominal aorta). The computer automatically generated the TAC.

Parameter calculation

The core parameter of this study is the RBPPR, calculated using the following formula:

RBPPR=KPH(kcps)×10000%NetInjectionCounts(kcpm)[1]

Where, KPH: peak count rate of renal perfusion curve (kcounts/s).

Note: the factor 10,000 converts minutes to seconds and scales the ratio to a convenient percentage. Derivation: (kcps/(kcpm/60)) ×5/3×100% = (kcps/kcpm) ×10,000%. The 5/3 coefficient is added for ease of calculation.

Net injection counts (kcpm): computed automatically by computer.

Statistical analysis

The software SPSS 27.0 (IBM Corp., Armonk, NY, USA) was used for analysis. Measurement data were expressed as x¯±s. Analysis of mixed-effects models was used for comparisons among multiple groups. For those with homogeneous variance, least significant difference (LSD) method was used for pairwise comparison; for those with heterogeneous variance, Dunnett T3 was used. Counting data were expressed as n (%), and the χ² test was used for comparison between groups. P value <0.05 was considered statistically significant. Spearman correlation analysis was used to evaluate the correlation between RBPPR and GFR. The diagnostic efficacy of RBPPR was evaluated through the receiver operating characteristic (ROC) curve. The results were independently evaluated by two senior nuclear medicine physicians, and the inter-observer consistency was good (the consistency of the diagnostic results was 94%, and kappa =0.79). For the cases with differences (n=9), a consensus was reached after consultation and discussion, and the final consensus result was included in the subsequent statistical analysis.

Results

Baseline statistical surveys of three groups (Table 1)

A total of 151 cases were ultimately included in this study, with a balanced gender distribution (75 males and 76 females, χ²=0.007, P=0.935). There was a significant difference in gender among the three groups of samples (χ²=7.642, P=0.022). No significant difference was identified in gender between the incomplete compensation group and the control group (P=0.132).

The age data of the three groups showed a slightly left-skewed distribution. The age difference in the completely compensated group was slightly larger, whereas that in the incomplete compensated group was relatively concentrated. There was no statistically significant difference in age among the three groups.

The differences among the three groups of ekGFR were statistically significant (F=94.123, P<0.001). The pairwise comparisons of the three groups showed significant differences P<0.001 (see Figure 1).

Figure 1 Distribution graphs and difference analysis of three groups of ekGFR and RBPPR. ***, P<0.001; ****, P<0.0001; ns, P>0.05. com, completely compensated group; con, control group; inc, incompletely compensated group. ekGFR, each kidney glomerular filtration rate; RBPPR, renal blood perfusion peak ratio.

There were significant differences (F=43.336, P<0.001) in the RBPPR levels among the three case groups. The RBPPR in the completely compensated group was the highest (5.20%±1.35%), with the largest internal variation [standard deviation (SD) 1.35], and the most concentrated within the incomplete compensated group (SD 0.66). Compared with the control group, the incomplete compensation group showed no significant statistical difference P=0.145, whereas the complete compensation group showed a significant difference P<0.001 (see Figure 1).

Correlation analysis of GFR and RBPPR in three groups

The Pearson’s correlation coefficient

Pearson’s correlation analysis of ekGFR and RBPPR in 205 kidneys of the three groups showed r=0.778>0.70, P<0.001, indicating that there is a strong positive correlation between RBPPR and ekGFR, which is extremely significant. Even after controlling for gender and age, a strong correlation remained (r=0.760, P<0.001), indicating that the correlation between RBPPR and renal function is independent of influence of age and gender, suggesting that RBPPR highly affects GFR. The scatter plot of the correlation between renal GFR and RBPPR showed that there is an approximately linear relationship between the two (Figure 2).

Figure 2 Scatter plot of RBPPR and GFR in 205 kidneys. ekGFR, each kidney glomerular filtration rate; GFR, glomerular filtration rate; RBPPR, renal blood perfusion peak ratio.

Analysis of diagnostic efficacy of RBPPR

ROC curve analysis of the diagnostic efficacy of RBPPR for renal function status showed the following (Table 2, Figure 3): For the diagnosis of complete renal function compensation, the optimal threshold was 3.620%, the area under the curve (AUC) was 0.842 [95% confidence interval (CI): 0.782–0.902], and the sensitivity was 91.6%.

Figure 3 Diagnostic efficacy map of RBPPR in the experimental group. RBPPR, renal blood perfusion peak ratio; ROC, receiver operating characteristic.

Discussion

Renal blood flow perfusion TAC depicts the dynamic changes of radioactive drugs in the kidney over time, and these changes are proportional to the renal blood flow (19-21). By analyzing TAC through appropriate mathematical models, the renal hemodynamic state can be indirectly monitored. Among them, the peak of TAC represents the maximum blood perfusion capacity of the kidney at that moment. The RBPPR model proposed in this study ingeniously uses “radioactive count rate (before injection − after injection)” as a standard factor, successfully eliminating the interference of individual differences in drug injection activity on the peak of TAC, and achieving the quantitative assessment of MAX-RP based on routine RDI examinations.

The results of this study show that RBPPR is concentratedly distributed within the three groups, with the maximum SD <1.35, indicating high stability of RBPPR. Except for no significant difference (P=0.145) between the incomplete compensation group and the control group, when comparing the other groups, RBPPR showed significant statistical differences (P<0.001). This confirmed that RBPPR not only can stably and quantitatively measure the maximum renal blood perfusion, but can also sensitively distinguish the maximum perfusion capacity under different pathological physiological conditions.

Although the ekGFR in both the complete compensation group and the incomplete compensation group was significantly higher than that in the control group, there was a significant difference in the growth degree of ekGFR between the two groups (P<0.001), and the ekGFR in the incomplete compensation group was significantly lower than that in the complete compensation group. Compared with the control group, the RBPPR in the incomplete compensation group did not increase significantly (P=0.145) with the significant increase of ekGFR (P<0.005) of the compensatory kidney as in the complete compensation group, presenting characteristics such as “growth divergence” and “lagging growth”.

The incomplete compensation group did not show the same synchronous increase in ekGFR and RBPPR as the complete compensation group. This indicates that RBPPR and GFR are not completely synchronized, suggesting that RBPPR affects the progression of GFR and plays a role as an initiating factor, thereby confirming the sequence of pathological changes. This phenomenon also validates the reliability of the research method used in this study. It shows that RBPPR is the main indicator for predicting whether GFR can be completely compensated, confirming that RBPPR can reflect the reserve compensatory capacity of the kidney and can be used as an important indicator for evaluating the reserve function of the kidney.

The RBPPR in 205 kidneys was strongly positively correlated with ekGFR (r=0.778, P<0.001), suggesting the accuracy of the model. It was also shown that the real-time maximum height of the kidney affects ekGFR.

ROC analysis further verified the clinical application value of RBPPR. Its sensitivity and specificity in the diagnosis of complete renal function compensation are both ideal, indicating that RBPPR is an excellent diagnostic indicator.

As a safe, non-invasive, low-radiation, and widely applied nuclear medicine technique, the introduction of the RBPPR model can extract more valuable hemodynamic parameters from routine images without adding additional examination burden, achieving “multi-dimensional assessment from a single examination” and contributing to more accurate diagnosis and evaluation of renal function in clinical practice.

This study has certain limitations. Firstly, because there is currently no routine method available for quantitatively measuring real-time maximum blood perfusion in clinical settings, this research lacks mature external validation checks. It was a single-center retrospective study, making it prone to selection bias. There were significant differences among the groups in terms of gender (this study is based on disease classification; it is possible that gender is an influencing factor for related diseases); Secondly, the sample size was relatively limited, and all examinations were once-off, lacking longitudinal data to verify its prognostic value. This study did not include special populations such as children and pregnant women, and the reference value range of RBPPR is still to be verified for special populations. The correlation between RBPPR and the results of renal pathological biopsy has not been analyzed, which makes it impossible to further clarify the relationship between RBPPR and the degree of renal parenchymal pathological damage. This study compared the control group with the experimental group in terms of both kidneys, and the statistical analysis was not independent. Subsequently, a multicenter, prospective large-sample study will be conducted to establish the reference value ranges of RBPPR for different populations and different disease types; a study on the correlation between RBPPR and renal pathological biopsy will be carried out to clarify the pathological basis that reflects renal parenchymal damage; a longitudinal follow-up study will be conducted to verify the prognostic evaluation value of RBPPR for the progression of renal function.

Conclusions

This study first proposed and verified the RBPPR model based on conventional RDI. This model can stably and quantitatively evaluate the real-time maximum blood perfusion of the kidney, is highly positively correlated with ekGFR, has good accuracy, and can sensitively reflect the hemodynamic changes of different renal function states. The optimal threshold of RBPPR for diagnosing complete compensation of renal function is 3.620%, with excellent diagnostic efficacy. It provides a simple and reliable new quantitative method for evaluating whether renal function can be completely compensated and the assessment of renal reserve function, and displays good clinical applicability.

Acknowledgments

We would like to express our sincere gratitude to all members of our department who participated in the preliminary work for this paper. We thank Xu Lei, Zeng You Shen, Wang Chongying, Zhou Mingming, Liu Shaoxian, Wang Xiaojuan, Wang Yanli, Zhu Yukang, Wang Luyao, and others from the Department of Nuclear Medicine for their data collection efforts. We also extend our gratitude to the hospital leadership and the Office of Research at the First Affiliated Hospital of Anhui University of Science and Technology for their support.

Footnote

Reporting Checklist: The authors have completed the STARD reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-2026-0704/rc

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2026-0704/dss

Funding: The study was supported by the 2025 Provincial Health and Wellness Science and Technology Projects (Provincial Population Health Foundation Projects—Hengrui Special Program (No. 2025BAj20004).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2026-0704/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. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of The First Affiliated Hospital of Anhui University of Science and Technology (approval No. 2024-KY-BY013), and individual consent for this retrospective analysis 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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