The new research, published in CVIR Oncology, pooled nine years of experience from three specialist centers in the United Kingdom, the United States, and Spain. The retrospective analysis drew on a prospectively maintained database of patients treated with percutaneous IRE between May 2015 and October 2024, using the NanoKnife 3.0 System. Every case involved a biopsy-proven renal cell carcinoma that a multidisciplinary tumor board had deemed unsuitable for partial or radical nephrectomy, or for conventional thermal ablation, typically because the tumor pressed against vital structures, sat within a solitary kidney, or the patient carried significant comorbidities.

The cohort comprised 68 patients with a mean age of 66.9 years, harboring 71 tumors with a mean diameter of 2.83 centimeters. These were not simple lesions: the median RENAL Nephrometry score, a standardized measure of anatomical complexity, was 9, placing them among the most challenging tumors treated anywhere. Nearly 58 percent were entirely endophytic, meaning they grew wholly within the kidney’s interior, and almost half were hilar tumors touching the renal artery or vein. Strikingly, 93 percent of the tumors lay less than one millimeter from a vital structure, including the ureter, colon, renal vessels, collecting system, and in rare cases the inferior vena cava, liver, small bowel, or spleen.

IRE works in a fundamentally different way from the radiofrequency, cryoablation, and microwave techniques that dominate image-guided ablation. Rather than heating or freezing tissue, the technology delivers high-voltage electrical impulses through fine needles placed around the tumor under ultrasound or CT guidance. These pulses create irreversible nanopores in the lipid membranes of cancer cells, disrupting cellular homeostasis, causing loss of intracellular contents and ultimately triggering apoptotic cell death. Crucially, the technique spares structures rich in collagen, such as ureters, blood vessels, and bile ducts, because their architecture does not depend on the cellular membranes that the pulses destroy. It also avoids the heat-sink effect, in which flowing blood dissipates thermal energy and undermines ablation near large vessels.

The procedure itself is technically demanding. Patients undergo general anesthesia with deep neuromuscular blockade to ensure complete muscle paralysis, since the electrical pulses would otherwise provoke violent contractions. Interventional radiologists, each with more than a decade of ablation experience, inserted an average of 4.56 monopolar electrodes to bracket each tumor. A test run of 20 pulses per electrode pair confirmed electrical conductivity, allowing adjustment of voltage to keep delivered current between 20 and 40 amperes, before the full treatment of 90 pulses per electrode pair was delivered with cardiac gating. Mean anesthesia time was 107 minutes, and patients typically stayed 1.6 days in hospital.

The headline results were encouraging. Technical success, meaning complete coverage of the tumor by the ablation zone, was achieved in 100 percent of sessions. Primary technique efficacy, defined as no residual enhancing tumor at the one-month scan, was 77.5 percent. While that figure trails some earlier single-center series, the authors emphasize that their tumors were larger and far more complex than those in comparable studies, and efficacy fell significantly as tumor size rose, particularly beyond 3.5 centimeters. Importantly, the modest primary efficacy did not translate into poor long-term cancer control: when residual disease was salvaged with a single additional ablation session, local control reached 95.8 percent, and five-year local tumor progression-free survival stood at 84.4 percent, rising to 81.1 percent at seven years.

Safety data were equally notable. Only two major adverse events occurred among 71 procedures, a rate of 2.8 percent: one permanent ureteric injury requiring long-term stenting and one episode of hematuria that resolved after stent removal. By comparison, published series of cryoablation for completely endophytic tumors report major complication rates approaching 10 percent, and robotic partial nephrectomy series report grade 3 or higher complications of around 17.5 percent. Kidney function was well preserved, with a mean decline in estimated glomerular filtration rate of just 7.5 ml/min/1.73m2, and only 10 percent of patients experiencing a clinically significant drop of more than 25 percent. Oncological durability was also reassuring, with cancer-specific survival of 98 percent at five years and metastasis-free survival of 91 percent.

Perhaps the most striking finding came from the composite ‘trifecta’ outcome, borrowed from surgical practice and combining primary efficacy, absence of major complications, and less than 25 percent decline in kidney function. IRE achieved the trifecta in 68.6 percent of cases, exceeding the 58.8 percent reported for thermal ablation and the 65.3 percent for robotic partial nephrectomy in comparable multicenter analyses of endophytic tumors. The authors suggest this may reflect IRE’s inherent suitability for tumors hugging critical structures, though they caution that head-to-head prospective comparisons are still needed before declaring superiority. They also describe practical refinements, including placing the electrode nearest a vital structure as the anode so pulses fire away from it, and using pre-operative ureteric stents in high-risk cases to guard against injury.

The study is not without limitations. It was retrospective, lacked a contemporaneous control group, involved only four operators across three centers, and did not employ centralized imaging review. Its results apply most directly to the kind of complex, high-risk tumors referred to specialist centers. Nevertheless, as the largest and longest-followed series of IRE for renal cancer to date, it provides the strongest real-world evidence yet that this electric-pulse technology deserves a firm place in the kidney cancer toolkit. For the growing population of patients with tumors once considered untreatable without sacrificing a kidney, the message from this nine-year, three-country experience is clear: irreversible electroporation can destroy the cancer while preserving both the organ and its function.

Subject of Research: Real-world outcomes of irreversible electroporation for complex small renal cell carcinomas unsuitable for surgery or thermal ablation

Article Title: MulticentRe rEal World outcomes of IrReversible Electroporation for complex small kiDney cancers (REWIRED)

Article References: MulticentRe rEal World outcomes of IrReversible Electroporation for complex small kiDney cancers (REWIRED). (n.d.). https://doi.org/10.1007/s44343-026-00049-z

Image Credits: AI Generated

DOI: 10.1007/s44343-026-00049-z

Keywords: irreversible electroporation, kidney cancer, renal cell carcinoma, image-guided ablation, small renal mass, NanoKnife, interventional radiology, nephron-sparing treatment, cryoablation, partial nephrectomy, RENAL nephrometry score, trifecta outcome

The research, led by Chih-Ying Huang and colleagues at Taipei Veterans General Hospital and National Yang Ming Chiao Tung University in Taiwan, set out to determine whether fully automated AI segmentation could extract meaningful three-dimensional volumetric features from routine pre-treatment CT scans and whether those features correlated with outcomes after cryoablation for renal cell carcinoma. Rather than asking radiologists to eyeball categorical scores, the team deployed two deep learning tools to do the measuring: TotalSegmentator, a robust open-source system capable of segmenting more than 100 anatomic structures in CT images, and a model developed for the 2023 Kidney and Tumor Segmentation Challenge (KiTS23). Both are built on the nnU-Net framework, a self-configuring deep learning architecture that has become a workhorse of modern biomedical image segmentation.

The technical workflow is deceptively simple. For each patient, the pre-treatment nephrographic-phase contrast-enhanced CT scan was fed into the segmentation pipeline, which generated masks for the kidneys, renal tumors, and renal cysts. Masks for the renal sinuses, the central fat-filled cavity of the kidney that houses the collecting system and major blood vessels, were produced through a geometry-based approach described in the study’s supplementary material. Once the masks were generated, the software extracted a series of quantitative 3D features: tumor volume, an automated RENAL nephrometry score, the minimum distance between tumor and renal sinus, and a novel metric called tumor-renal sinus contact area, which quantifies the surface area over which the tumor directly abuts the renal sinus. On a GPU-accelerated workstation, the entire process took approximately five minutes per case, with an additional five minutes when manual correction was needed.

That manual correction proved to be the exception rather than the rule. Of the 116 patients in the study, only 16 required any adjustment to the automated masks, and most of those involved tumors lying adjacent to renal cysts or cases in which the algorithm failed to identify the tumor at all. No case required complete re-segmentation. This level of automation matters because conventional nephrometry scores suffer from well-documented interobserver variability. The R component of the RENAL score, for example, is measured on orthogonal planes and may not reflect the true maximal three-dimensional extent of a tumor, while the exophytic and location components have shown low perfect agreement among human readers. Continuous volumetric features extracted by software sidestep both problems, offering objective, reproducible numbers that capture anatomy in its full spatial complexity.

The study cohort consisted of 116 patients who underwent CT-guided percutaneous cryoablation for renal lesions at a single center between October 2009 and December 2024. The group comprised 85 men and 31 women with a mean age of 70.7 years, and the mean follow-up duration was 2.8 years. The mean tumor volume was 15.1 milliliters and the mean tumor diameter was 3.6 centimeters, consistent with the small, early-stage lesions for which ablation is typically recommended. Clear cell renal cell carcinoma was the most common histologic subtype, accounting for 64.7 percent of tumors. Notably, all cryoablation procedures throughout the fifteen-year inclusion window were performed by a single operator, which the authors suggest may have reduced variability related to procedural technique even as practice patterns evolved.

The clinical outcomes were assessed using standardized definitions from the International Working Group on Image-Guided Tumor Ablation and the SIO and DATECAN consensus guidelines. At the first post-ablation follow-up, 94 percent of patients achieved complete ablation, while 6 percent had residual unablated tumor requiring repeat cryoablation. Among those with complete initial ablation, 8 patients, or 6.9 percent of the cohort, later developed local tumor progression at the ablation margin. One patient with persistent tumor after re-ablation was ultimately found to have suspected venous invasion and a new lesion in the same kidney, requiring systemic therapy. To capture both early failure and later progression, the researchers defined a composite endpoint of local tumor control failure, combining residual unablated tumor and local tumor progression.

The statistical results pointed emphatically toward one feature. In univariable logistic regression, tumor volume, the RENAL nephrometry score, its R component, and tumor-renal sinus contact area were all significantly associated with local tumor control failure. But in a deliberately parsimonious multivariable model, limited by only 15 outcome events and bolstered by bootstrap resampling with 1,000 iterations to confirm coefficient stability, only tumor-renal sinus contact area remained independently predictive, with an odds ratio of 1.379 and a p-value of 0.002. The authors derived a composite risk score, calculated as 0.321 times the tumor-renal sinus contact area plus 0.023 times the tumor volume. In receiver operating characteristic analysis, this score achieved an area under the curve of 0.765 for predicting local tumor control failure, numerically higher than the 0.664 achieved by the RENAL nephrometry score, although the difference did not reach statistical significance on the DeLong test. With an optimal cutoff of 1.51, the score yielded a sensitivity of 67 percent and a specificity of 86 percent.

Two representative cases illustrate the score’s clinical texture. A 65-year-old man with biopsy-proven clear cell renal cell carcinoma had a 21.3-milliliter tumor with a tumor-renal sinus contact area of just 0.31 square centimeters, producing a risk score of 0.59, well below the cutoff. He underwent cryoablation and remained stable on follow-up imaging for more than four years. By contrast, a 91-year-old man with a similarly sized tumor of 25.2 milliliters but a contact area of 9.23 square centimeters scored 3.54, far above the threshold, and developed local tumor progression just nine months after treatment. In the Cox proportional hazards analysis, larger tumor-renal sinus contact area was also significantly associated with local tumor progression among patients who had achieved complete initial ablation, with a hazard ratio of 1.255 and a p-value of 0.026.

Why should contact with the renal sinus matter so much? The authors offer a biologically plausible but unproven explanation: the renal sinus contains major blood vessels whose continuous blood flow can dissipate cold energy from the ablation zone, a phenomenon known as the cold-sink effect. Tumors with extensive contact along the tumor-sinus interface may therefore be more susceptible to incomplete freezing, and indeed, viable tumor foci identified on follow-up imaging in this cohort were frequently located adjacent to the renal sinus. The researchers caution that this mechanism remains a hypothesis, since the study did not directly evaluate renal sinus vascular anatomy, tissue perfusion, intraprocedural temperature distribution, or ablation margin adequacy. Even so, the finding suggests that automated segmentation can capture an anatomically meaningful feature that is nearly impossible to quantify visually, information that existing categorical scoring systems simply do not encode.

The authors are careful to frame their conclusions as exploratory. The study was retrospective and single-center, the number of outcome events was small, the AI segmentation tools have not yet been formally validated across institutions and imaging protocols, and the composite risk score has not undergone external validation. Its discriminative performance was only moderate, and its incremental value over conventional predictors should be interpreted cautiously. Still, the implications are tantalizing. An objective, automated risk score generated in minutes from an existing CT scan could help clinicians identify anatomically challenging tumors, guide patient selection between ablation and surgery, and tailor surveillance intensity, with higher-risk patients potentially benefiting from closer imaging follow-up. Future work, the authors suggest, may extend the approach to segment renal vessels and ablation zones, register pre-treatment and intraprocedural images, and quantitatively assess ablation margins, bringing the field closer to a fully computational framework for predicting and ultimately preventing local treatment failure in kidney cancer.

Subject of Research: AI-based automated segmentation-derived 3D volumetric imaging features and outcomes after cryoablation for renal cell carcinoma

Article Title: Association between AI-based automated segmentation-derived 3D volumetric imaging features and outcomes after cryoablation for renal cell carcinoma

Article References: Huang, C.-Y., Hong, J.-A., Chang, N.-W., Li, C.-C., Liu, C.-A., & Shen, S.-H. (2026). Association between AI-based automated segmentation-derived 3D volumetric imaging features and outcomes after cryoablation for renal cell carcinoma. CVIR Oncology, 2(1), Article 24. https://doi.org/10.1007/s44343-026-00053-3

Image Credits: AI Generated

DOI: 10.1007/s44343-026-00053-3

Keywords: renal cell carcinoma, cryoablation, artificial intelligence, automated segmentation, 3D volumetric imaging, tumor-renal sinus contact area, RENAL nephrometry score, tumor ablation, risk score, kidney cancer, radiology, predictive modeling