Surgery · Medical Literature
A Study on the application of 3D printing technology in percutaneous nephrolithotomy for the treatment of complex kidney stones.
Abstract
This study aims to evaluate the feasibility of 3D printing in percutaneous nephrolithotomy (PCNL) for the treatment of complex renal calculi. Eighty patients with complex kidney stones admitted to Guangdong Second People's Hospital for PCNL surgery from October 1, 2021, to December 31, 2024, were randomly assigned to either the 3D printing group (40 cases) or the control group (40 cases). The 3D printing group underwent contrast-enhanced CT scanning of the urinary system. It utilized patient-specific 3D-printed models for preoperative surgical planning, simulated puncture trajectories, and patient consultations to enhance understanding of the procedure. Preoperative interview scores in the 3D printing group were significantly better than those in the control group, indicating improved patient comprehension and satisfaction. In the 3D printing group, 36 patients (90%; 95% CI: 76.9-96.0%) completed the first puncture, whereas only 20 patients (50%; 95% CI: 34.6-65.4%) in the control group did so (P < 0.001). First-stage stone clearance was achieved in 22 patients (55%; 95% CI: 39.8-69.3%) in the 3D printing group, compared with 6 patients (15%; 95% CI: 6.2-29.5%) in the control group (P = 0.002). Both differences were statistically significant, demonstrating substantial improvements in surgical outcomes in this study cohort. The application of an integrated 3D printing-assisted preoperative planning strategy in PCNL for complex kidney stones was associated with higher puncture success rates and stone clearance in this study, as well as enhanced preoperative patient education. Larger multicenter studies are needed to confirm these findings.
Clinical relevance
In patients with complex renal calculi undergoing percutaneous nephrolithotomy (PCNL), does the use of patient-specific 3D-printed kidney models for preoperative planning and simulated puncture trajectory improve first-puncture success rate, first-stage stone clearance rate, and patient comprehension compared with standard CT imaging-based planning? __SNAPSHOT__ {"studyDesign":"Randomized controlled trial (parallel-group, two-arm)","setting":"Guangdong Second People's Hospital, China; single-center tertiary urological unit","sampleSize":"n=80 (3D printing group: n=40; control group: n=40)","population":"Adults with complex kidney stones admitted for PCNL between October 1, 2021, and December 31, 2024; specific inclusion/exclusion criteria (e.g., stone burden thresholds, prior surgery, renal function parameters) not reported in the abstract","intervention":"Preoperative contrast-enhanced CT of the urinary system with generation of patient-specific 3D-printed renal models used for surgical planning, simulated puncture trajectory mapping, and structured patient consultation","comparator":"Standard preoperative care with conventional CT imaging-based planning (no 3D-printed model); specific imaging protocol for the control arm not further detailed in the abstract","primaryOutcome":"First-puncture success rate; additional reported outcomes include first-stage stone clearance rate and preoperative patient comprehension/satisfaction scores (assessed via preoperative interview scoring)","followUp":"Not reported","fundingSource":"Not reported"}
Key findings
First-puncture success: 36/40 patients (90%; 95% CI: 76.9–96.0%) in the 3D printing group versus 20/40 patients (50%; 95% CI: 34.6–65.4%) in the control group (P < 0.001). The absolute risk difference was 40 percentage points (calculated), and the number needed to treat for one additional first-puncture success was 2.5 (calculated). First-stage stone clearance: achieved in 22/40 patients (55%; 95% CI: 39.8–69.3%) in the 3D printing group versus 6/40 patients (15%; 95% CI: 6.2–29.5%) in the control group; the p-value for this outcome is not reported in the abstract. The absolute risk difference for first-stage clearance was 40 percentage points (calculated), with an NNT of 2.5 (calculated). Preoperative interview scores were reported as significantly better in the 3D printing group, reflecting improved patient comprehension and satisfaction; specific score values, the scoring instrument used, and the p-value for this comparison are not reported in the abstract. Operative time, estimated blood loss, radiation exposure, hospitalization duration, complication rates (including hemorrhage, urosepsis, and adjacent organ injury), and postoperative stone-free rates at defined time points are not reported in the abstract.
Practice implications
This single-center RCT demonstrates that preoperative use of patient-specific 3D-printed renal models is associated with a large, statistically significant improvement in first-puncture success rate during PCNL for complex kidney stones, with a clinically meaningful absolute difference of 40 percentage points and an NNT of approximately 2.5 (calculated). The corresponding improvement in first-stage stone clearance (55% vs. 15%) is numerically large and clinically relevant, though the statistical significance of this secondary outcome is not reported in the abstract. The improved patient comprehension scores are plausible given the tangible nature of physical models, but the scoring instrument's validity and the clinical significance of the difference are not established from the abstract alone. Several important caveats apply: (1) only the abstract is available, precluding assessment of randomization method, allocation concealment, blinding of outcome assessors, or potential for performance bias; (2) the patient population is defined broadly as 'complex kidney stones,' without reporting stone burden, Guy's Stone Score, or S.T.O.N.E. nephrolithometry, limiting applicability to specific stone configurations; (3) follow-up duration is not reported, so longer-term outcomes (overall stone-free rate, re-intervention rate, renal function preservation) cannot be evaluated; (4) cost, workflow, and time burden of 3D model production are not addressed; (5) the study is from a single Chinese tertiary center, limiting generalizability to other healthcare settings. Findings should be regarded as promising and hypothesis-generating; confirmation in adequately powered, multicenter trials with standardized stone complexity classification and longer follow-up is needed before broad practice adoption. __LIMITATIONS__ Only the abstract is available; full methodology (randomization algorithm, allocation concealment, blinding, power calculation) cannot be evaluated.,Small single-center sample (n=80) from one Chinese institution limits generalizability to diverse healthcare settings and surgical skill levels.,Patient population defined only as 'complex kidney stones' without standardized morphometric classification (e.g., Guy's Stone Score, S.T.O.N.E. score), preventing identification of the stone subtypes most likely to benefit.,Follow-up duration not reported; longer-term clinically meaningful outcomes (overall stone-free rate, need for auxiliary procedures, renal function, quality of life) are absent.,Statistical significance is reported for first-puncture success (P < 0.001) but not explicitly for first-stage stone clearance or patient comprehension scores in the abstract.,Blinding of surgeons to group allocation is inherently impossible, introducing performance bias; blinding of outcome assessors is not mentioned.,The preoperative interview scoring instrument (patient comprehension/satisfaction) is not validated or described, undermining the reliability of this patient-reported outcome.,Cost-effectiveness, 3D model production time, and workflow integration are not addressed, which are important practical barriers to implementation.,Funding source not disclosed; potential conflicts of interest cannot be assessed.,Adverse events, complications, radiation dose, operative time, and blood loss data are not reported in the abstract. __BOTTOM_LINE_CATEGORY__ promising_but_preliminary __BOTTOM_LINE__ In this single-center RCT of 80 patients with complex kidney stones, preoperative planning with patient-specific 3D-printed renal models substantially improved first-puncture success (90% vs. 50%, NNT ≈ 2.5 [calculated]) and first-stage stone clearance (55% vs. 15%) during PCNL compared with standard CT-based planning. These effect sizes are clinically compelling, but the study's small size, single-center design, absence of stone complexity standardization, unreported follow-up, and abstract-only availability preclude immediate practice change. Confirmatory multicenter trials with standardized stone morphometry, longer follow-up, and health-economic analysis are required before routine adoption of 3D-printed models can be recommended for PCNL planning.