Complications and adverse events in lymphadenectomy of the inguinal area: worldwide expert consensus.

BACKGROUND: Inguinal lymph node dissection plays an important role in the management of melanoma, penile and vulval cancer. Inguinal lymph node dissection is associated with various intraoperative and postoperative complications with significant heterogeneity in classification and reporting. This lack of standardization challenges efforts to study and report inguinal lymph node dissection outcomes. The aim of this study was to devise a system to standardize the classification and reporting of inguinal lymph node dissection perioperative complications by creating a worldwide collaborative, the complications and adverse events in lymphadenectomy of the inguinal area (CALI) group. METHODS: A modified 3-round Delphi consensus approach surveyed a worldwide group of experts in inguinal lymph node dissection for melanoma, penile and vulval cancer. The group of experts included general surgeons, urologists and oncologists (gynaecological and surgical). The survey assessed expert agreement on inguinal lymph node dissection perioperative complications. Panel interrater agreement and consistency were assessed as the overall percentage agreement and Cronbach's α. RESULTS: Forty-seven experienced consultants were enrolled: 26 (55.3%) urologists, 11 (23.4%) surgical oncologists, 6 (12.8%) general surgeons and 4 (8.5%) gynaecology oncologists. Based on their expertise, 31 (66%), 10 (21.3%) and 22 (46.8%) of the participants treat penile cancer, vulval cancer and melanoma using inguinal lymph node dissection respectively; 89.4% (42 of 47) agreed with the definitions and inclusion as part of the inguinal lymph node dissection intraoperative complication group, while 93.6% (44 of 47) agreed that postoperative complications should be subclassified into five macrocategories. Unanimous agreement (100%, 37 of 37) was achieved with the final standardized classification system for reporting inguinal lymph node dissection complications in melanoma, vulval cancer and penile cancer. CONCLUSION: The complications and adverse events in lymphadenectomy of the inguinal area classification system has been developed as a tool to standardize the assessment and reporting of complications during inguinal lymph node dissection for the treatment of melanoma, vulval and penile cancer.

PCa-RadHop: A transparent and lightweight feed-forward method for clinically significant prostate cancer segmentation.

Prostate Cancer is one of the most frequently occurring cancers in men, with a low survival rate if not early diagnosed. PI-RADS reading has a high false positive rate, thus increasing the diagnostic incurred costs and patient discomfort. Deep learning (DL) models achieve a high segmentation performance, although require a large model size and complexity. Also, DL models lack of feature interpretability and are perceived as "black-boxes" in the medical field. PCa-RadHop pipeline is proposed in this work, aiming to provide a more transparent feature extraction process using a linear model. It adopts the recently introduced Green Learning (GL) paradigm, which offers a small model size and low complexity. PCa-RadHop consists of two stages: Stage-1 extracts data-driven radiomics features from the bi-parametric Magnetic Resonance Imaging (bp-MRI) input and predicts an initial heatmap. To reduce the false positive rate, a subsequent stage-2 is introduced to refine the predictions by including more contextual information and radiomics features from each already detected Region of Interest (ROI). Experiments on the largest publicly available dataset, PI-CAI, show a competitive performance standing of the proposed method among other deep DL models, achieving an area under the curve (AUC) of 0.807 among a cohort of 1,000 patients. Moreover, PCa-RadHop maintains orders of magnitude smaller model size and complexity.

A nomogram to predict the absence of clinically significant prostate cancer in males with negative MRI

ABSTRACT Purpose: To create a nomogram to predict the absence of clinically significant prostate cancer (CSPCa) in males with non-suspicion multiparametric magnetic resonance imaging (mpMRI) undergoing prostate biopsy (PBx). Materials and Methods: We identified consecutive patients who underwent 3T mpMRI followed by PBx for suspicion of PCa or surveillance follow-up. All patients had Prostate Imaging Reporting and Data System score 1-2 (negative mpMRI). CSPCa was defined as Grade Group ≥2. Multivariate logistic regression analysis was performed via backward elimination. Discrimination was evaluated with area under the receiver operating characteristic (AUROC). Internal validation with 1,000x bootstrapping for estimating the optimism corrected AUROC. Results: Total 327 patients met inclusion criteria. The median (IQR) age and PSA density (PSAD) were 64 years (58-70) and 0.10 ng/mL2 (0.07-0.15), respectively. Biopsy history was as follows: 117 (36%) males were PBx-naive, 130 (40%) had previous negative PBx and 80 (24%) had previous positive PBx. The majority were White (65%); 6% of males self-reported Black. Overall, 44 (13%) patients were diagnosed with CSPCa on PBx. Black race, history of previous negative PBx and PSAD ≥0.15ng/mL2 were independent predictors for CSPCa on PBx and were included in the nomogram. The AUROC of the nomogram was 0.78 and the optimism corrected AUROC was 0.75. Conclusions: Our nomogram facilitates evaluating individual probability of CSPCa on PBx in males with PIRADS 1-2 mpMRI and may be used to identify those in whom PBx may be safely avoided. Black males have increased risk of CSPCa on PBx, even in the setting of PIRADS 1-2 mpMRI

Accuracy, readability, and understandability of large language models for prostate cancer information to the public.

BACKGROUND: Generative Pretrained Model (GPT) chatbots have gained popularity since the public release of ChatGPT. Studies have evaluated the ability of different GPT models to provide information about medical conditions. To date, no study has assessed the quality of ChatGPT outputs to prostate cancer related questions from both the physician and public perspective while optimizing outputs for patient consumption. METHODS: Nine prostate cancer-related questions, identified through Google Trends (Global), were categorized into diagnosis, treatment, and postoperative follow-up. These questions were processed using ChatGPT 3.5, and the responses were recorded. Subsequently, these responses were re-inputted into ChatGPT to create simplified summaries understandable at a sixth-grade level. Readability of both the original ChatGPT responses and the layperson summaries was evaluated using validated readability tools. A survey was conducted among urology providers (urologists and urologists in training) to rate the original ChatGPT responses for accuracy, completeness, and clarity using a 5-point Likert scale. Furthermore, two independent reviewers evaluated the layperson summaries on correctness trifecta: accuracy, completeness, and decision-making sufficiency. Public assessment of the simplified summaries' clarity and understandability was carried out through Amazon Mechanical Turk (MTurk). Participants rated the clarity and demonstrated their understanding through a multiple-choice question. RESULTS: GPT-generated output was deemed correct by 71.7% to 94.3% of raters (36 urologists, 17 urology residents) across 9 scenarios. GPT-generated simplified layperson summaries of this output was rated as accurate in 8 of 9 (88.9%) scenarios and sufficient for a patient to make a decision in 8 of 9 (88.9%) scenarios. Mean readability of layperson summaries was higher than original GPT outputs ([original ChatGPT v. simplified ChatGPT, mean (SD), p-value] Flesch Reading Ease: 36.5(9.1) v. 70.2(11.2), <0.0001; Gunning Fog: 15.8(1.7) v. 9.5(2.0), p < 0.0001; Flesch Grade Level: 12.8(1.2) v. 7.4(1.7), p < 0.0001; Coleman Liau: 13.7(2.1) v. 8.6(2.4), 0.0002; Smog index: 11.8(1.2) v. 6.7(1.8), <0.0001; Automated Readability Index: 13.1(1.4) v. 7.5(2.1), p < 0.0001). MTurk workers (n = 514) rated the layperson summaries as correct (89.5-95.7%) and correctly understood the content (63.0-87.4%). CONCLUSION: GPT shows promise for correct patient education for prostate cancer-related contents, but the technology is not designed for delivering patients information. Prompting the model to respond with accuracy, completeness, clarity and readability may enhance its utility when used for GPT-powered medical chatbots.

Generative artificial intelligence in surgery.

Generative artificial intelligence is able to collect, extract, digest, and generate information in an understandable way for humans. As the first surgical applications of generative artificial intelligence are applied, this perspective paper aims to provide a comprehensive overview of current applications and future perspectives for the application of generative artificial intelligence in surgery, from preoperative planning to training. Generative artificial intelligence can be used before surgery for planning and decision support by extracting patient information and providing patients with information and simulation regarding the procedure. Intraoperatively, generative artificial intelligence can document data that is normally not captured as intraoperative adverse events or provide information to help decision-making. Postoperatively, GAIs can help with patient discharge and follow-up. The ability to provide real-time feedback and store it for later review is an important capability of GAIs. GAI applications are emerging as highly specialized, task-specific tools for tasks such as data extraction, synthesis, presentation, and communication within the realm of surgery. GAIs have the potential to play a pivotal role in facilitating interaction between surgeons and artificial intelligence.

Study protocol for the Intraoperative Complications Assessment and Reporting with Universal Standards (ICARUS) global cross-specialty surveys and consensus.

Annually, about 300 million surgeries lead to significant intraoperative adverse events (iAEs), impacting patients and surgeons. Their full extent is underestimated due to flawed assessment and reporting methods. Inconsistent adoption of new grading systems and a lack of standardization, along with litigation concerns, contribute to underreporting. Only half of relevant journals provide guidelines on reporting these events, with a lack of standards in surgical literature. To address these issues, the Intraoperative Complications Assessment and Reporting with Universal Standard (ICARUS) Global Surgical Collaboration was established in 2022. The initiative involves conducting global surveys and a Delphi consensus to understand the barriers for poor reporting of iAEs, validate shared criteria for reporting, define iAEs according to surgical procedures, evaluate the existing grading systems' reliability, and identify strategies for enhancing the collection, reporting, and management of iAEs. Invitation to participate are extended to all the surgical specialties, interventional cardiology, interventional radiology, OR Staffs and anesthesiology. This effort represents an essential step towards improved patient safety and the well-being of healthcare professionals in the surgical field.

Prophylactic Use of Biologic Mesh in Ileal Conduit (PUBMIC): A Randomized Clinical Trial.

PURPOSE: We assessed the effect of prophylactic biologic mesh on parastomal hernia (PSH) development in patients undergoing cystectomy and ileal conduit (IC). MATERIALS AND METHODS: This phase 3, randomized, controlled trial (NCT02439060) included 146 patients who underwent cystectomy and IC at the University of Southern California between 2015 and 2021. Follow-ups were physical exam and CT every 4 to 6 months up to 2 years. Patients were randomized 1:1 to receive FlexHD prophylactic biological mesh using sublay intraperitoneal technique vs standard IC. The primary end point was time to radiological PSH, and secondary outcomes included clinical PSH with/without surgical intervention and mesh-related complications. RESULTS: The 2 arms were similar in terms of baseline clinical features. All surgeries and mesh placements were performed without any intraoperative complications. Median operative time was 31 minutes longer in patients who received mesh, yet with no statistically significant difference (363 vs 332 minutes, P = .16). With a median follow-up of 24 months, radiological and clinical PSHs were detected in 37 (18 mesh recipients vs 19 controls) and 16 (8 subjects in both arms) patients, with a median time to radiological and clinical PSH of 8.3 and 15.5 months, respectively. No definite mesh-related adverse events were reported. Five patients (3 in the mesh and 2 in the control arm) required surgical PSH repair. Radiological PSH-free survival rates in the mesh and control groups were 74% vs 75% at 1 year and 69% vs 62% at 2 years. CONCLUSIONS: Implementation of biologic mesh at the time of IC construction is safe without significant protective effects within 2 years following surgery.

Neuronally differentiated macula densa cells regulate tissue remodeling and regeneration in the kidney.

Tissue regeneration is limited in several organs, including the kidney, contributing to the high prevalence of kidney disease globally. However, evolutionary and physiological adaptive responses and the presence of renal progenitor cells suggest an existing remodeling capacity. This study uncovered endogenous tissue remodeling mechanisms in the kidney that were activated by the loss of body fluid and salt and regulated by a unique niche of a minority renal cell type called the macula densa (MD). Here, we identified neuronal differentiation features of MD cells that sense the local and systemic environment and secrete angiogenic, growth, and extracellular matrix remodeling factors, cytokines and chemokines, and control resident progenitor cells. Serial intravital imaging, MD nerve growth factor receptor and Wnt mouse models, and transcriptome analysis revealed cellular and molecular mechanisms of these MD functions. Human and therapeutic translation studies illustrated the clinical potential of MD factors, including CCN1, as a urinary biomarker and therapeutic target in chronic kidney disease. The concept that a neuronally differentiated key sensory and regulatory cell type responding to organ-specific physiological inputs controls local progenitors to remodel or repair tissues may be applicable to other organs and diverse tissue-regenerative therapeutic strategies.

The effect of enhanced recovery after surgery on oncologic outcome following radical cystectomy for urothelial bladder carcinoma.

INTRODUCTION: Limited data are available regarding the effect of enhanced recovery after surgery (ERAS) protocols on the long-term outcomes of radical cystectomy (RC) in bladder cancer patients. The aim of this study is to evaluate the oncological outcomes in patients who underwent RC with ERAS protocol. METHODS: We reviewed the records of patients who underwent RC for primary urothelial bladder carcinoma with curative intent from January 2003 to August 2022. The primary and secondary outcomes were recurrence-free (RFS) and overall survival (OS). Multivariable Cox regression analysis was performed to evaluate the effect of ERAS on oncological outcomes. RESULTS: A total of 967 ERAS patients and 1144 non-ERAS patients were included in this study. The RFS rates at 1, 3, and 5 years after RC were 81%, 71.5%, and 69% in the ERAS cohort, respectively. This rate in the non-ERAS group was 81%, 71%, and 67% at 1, 3, and 5 years after RC, respectively (P = 0.50). However, ERAS patients had significantly better OS with 86%, 73%, and 67% survival rates at 1, 3, and 5 years compared to 84%, 68%, and 59.5% survival rates in the non-ERAS group, respectively (P = 0.002). In multivariable analysis adjusting for other relevant factors, ERAS was no longer independently associated with recurrence-free (HR = 0.96, 95% CI 0.76-1.22, P = 0.75) or overall survival (HR = 0.84, 95% CI 0.66-1.09, P = 0.28) following RC. CONCLUSION: ERAS protocols are associated with a shorter hospital stay, yet with no impact on long-term oncologic outcomes in patients undergoing RC for bladder cancer.

Blood-based liquid biopsy: A promising noninvasive test in diagnosis, surveillance, and prognosis of patients with upper tract urothelial carcinoma.

OBJECTIVES: To assess the efficacy of blood-based liquid biopsy in the diagnosis, surveillance, and prognosis of upper tract urothelial carcinoma (UTUC). METHODS AND MATERIALS: In this prospective study, peripheral blood samples were collected from patients with primary UTUC before surgery with curative intent and follow-up visits at University of Southern California between May 2021 and September 2022. The samples were analyzed using the third-generation comprehensive high-definition single-cell assay (HDSCA3.0) to detect rare events, including circulating tumor cells (CTCs) and oncosomes, based on the immunofluorescence signals of DAPI (D), cytokeratin (CK), CD45/CD31 (CD), and vimentin (V). The findings of pre-surgery liquid biopsies were compared with those of blood samples from normal donors (NDs) and matched follow-up liquid biopsies. The association between liquid biopsy findings and clinical data, including recurrence-free survival (RFS), was also assessed. RESULTS: Twenty-eight patients with UTUC were included, of whom 21 had follow-up samples. Significant differences in specific rare analytes were detected in the preoperative samples compared to the NDs. In the post- vs. presurgery matched analysis, a significant decrease was detected in total-, CK-, and CK|V oncosomes, as well as in D-, D|V-, and D|V|CD cells. With a median follow-up of 11 months, 8 patients had disease recurrence. Survival analysis demonstrated that patients with >1.95 preoperative CK|V oncosomes (p = 0.020) and those with >4.18 D|CK|V cells (p = 0.050) had worse RFS compared to other patients. CONCLUSIONS: This study demonstrated promising initial evidence for the biomarker role of CTCs and oncosomes in the diagnosis and surveillance of patients with UTUC.

Publishers' and journals' instructions to authors on use of generative artificial intelligence in academic and scientific publishing: bibliometric analysis.

OBJECTIVES: To determine the extent and content of academic publishers' and scientific journals' guidance for authors on the use of generative artificial intelligence (GAI). DESIGN: Cross sectional, bibliometric study. SETTING: Websites of academic publishers and scientific journals, screened on 19-20 May 2023, with the search updated on 8-9 October 2023. PARTICIPANTS: Top 100 largest academic publishers and top 100 highly ranked scientific journals, regardless of subject, language, or country of origin. Publishers were identified by the total number of journals in their portfolio, and journals were identified through the Scimago journal rank using the Hirsch index (H index) as an indicator of journal productivity and impact. MAIN OUTCOME MEASURES: The primary outcomes were the content of GAI guidelines listed on the websites of the top 100 academic publishers and scientific journals, and the consistency of guidance between the publishers and their affiliated journals. RESULTS: Among the top 100 largest publishers, 24% provided guidance on the use of GAI, of which 15 (63%) were among the top 25 publishers. Among the top 100 highly ranked journals, 87% provided guidance on GAI. Of the publishers and journals with guidelines, the inclusion of GAI as an author was prohibited in 96% and 98%, respectively. Only one journal (1%) explicitly prohibited the use of GAI in the generation of a manuscript, and two (8%) publishers and 19 (22%) journals indicated that their guidelines exclusively applied to the writing process. When disclosing the use of GAI, 75% of publishers and 43% of journals included specific disclosure criteria. Where to disclose the use of GAI varied, including in the methods or acknowledgments, in the cover letter, or in a new section. Variability was also found in how to access GAI guidelines shared between journals and publishers. GAI guidelines in 12 journals directly conflicted with those developed by the publishers. The guidelines developed by top medical journals were broadly similar to those of academic journals. CONCLUSIONS: Guidelines by some top publishers and journals on the use of GAI by authors are lacking. Among those that provided guidelines, the allowable uses of GAI and how it should be disclosed varied substantially, with this heterogeneity persisting in some instances among affiliated publishers and journals. Lack of standardization places a burden on authors and could limit the effectiveness of the regulations. As GAI continues to grow in popularity, standardized guidelines to protect the integrity of scientific output are needed.

Conditional generative learning for medical image imputation.

Image imputation refers to the task of generating a type of medical image given images of another type. This task becomes challenging when the difference between the available images, and the image to be imputed is large. In this manuscript, one such application is considered. It is derived from the dynamic contrast enhanced computed tomography (CECT) imaging of the kidneys: given an incomplete sequence of three CECT images, we are required to impute the missing image. This task is posed as one of probabilistic inference and a generative algorithm to generate samples of the imputed image, conditioned on the available images, is developed, trained, and tested. The output of this algorithm is the "best guess" of the imputed image, and a pixel-wise image of variance in the imputation. It is demonstrated that this best guess is more accurate than those generated by other, deterministic deep-learning based algorithms, including ones which utilize additional information and more complex loss terms. It is also shown that the pixel-wise variance image, which quantifies the confidence in the reconstruction, can be used to determine whether the result of the imputation meets a specified accuracy threshold and is therefore appropriate for a downstream task.

Survival of Patients with Chronic Kidney Disease Treated with Radical Cystectomy and Risk Factors of Glomerular Filtration Rate Loss Following Radical Cystectomy: Two Systematic Reviews and Meta-analyses of Interplay Between Radical Cystectomy and Renal Function.

CONTEXT: There is no high-level evidence regarding the risk factors of glomerular filtration rate (GFR) loss following radical cystectomy (RC) and survival outcomes of patients with chronic kidney disease (CKD) undergoing RC. OBJECTIVE: To identify the risk factors of CKD in patients treated with RC for bladder cancer and to assess overall and oncological survival of patients with CKD who underwent RC. EVIDENCE ACQUISITION: According to the Preferred Reporting Items for Systematic Reviews and Meta-analyses statement, two systematic reviews were performed for studies published before September 30, 2022, assessing (1) risk factors of renal function (RF) decline following RC and (2) overall and oncological outcomes of CKD patients treated with RC. EVIDENCE SYNTHESIS: A total of 21 and 17 studies were included for qualitative and quantitative syntheses, respectively. The first meta-analysis of ten studies (15 502 patients) identified these factors to be significantly associated with GFR loss following RC: advanced age, lower baseline RF, higher Charlson Comorbidity Index (CCI), diabetes mellitus, hypertension, postoperative hydronephrosis, ureteroenteric stricture, and locally advanced disease (hazard ratios [HRs] 1.03, 1.22, 1.5, 1.27, 1.24, 1.69, 1.92, and 5.13, respectively), while sex, preoperative hydronephrosis, perioperative chemotherapy, and diversion type were not. The second meta-analysis of seven studies (6900 patients) demonstrated significantly worse metastasis-free, cancer-specific, and overall survival in patients with higher CKD stages than in those with lower stages (HRs 1.54, 2.09, and 1.47, respectively). CONCLUSIONS: Current evidence suggests that older age, lower baseline RF, higher CCI, diabetes mellitus, hypertension, postoperative hydronephrosis, ureteroenteric stricture, and locally advanced disease are associated with long-term GFR loss following RC. In addition, patients with higher stages of CKD have worse long-term overall and oncological outcomes following RC. These data may help in counseling and decision-making regarding therapy and preventive measures. PATIENT SUMMARY: Several factors have been identified that can help identify patients at risk for glomerular filtration rate loss after radical cystectomy (RC). Chronic kidney disease is associated with poor cancer- and non-cancer-specific outcomes following RC.

A nomogram to predict the absence of clinically significant prostate cancer in males with negative MRI

PURPOSE: To create a nomogram to predict the absence of clinically significant prostate cancer (CSPCa) in males with non-suspicion multiparametric magnetic resonance imaging (mpMRI) undergoing prostate biopsy (PBx). MATERIALS AND METHODS: We identified consecutive patients who underwent 3T mpMRI followed by PBx for suspicion of PCa or surveillance follow-up. All patients had Prostate Imaging Reporting and Data System score 1-2 (negative mpMRI). CSPCa was defined as Grade Group ≥2. Multivariate logistic regression analysis was performed via backward elimination. Discrimination was evaluated with area under the receiver operating characteristic (AUROC). Internal validation with 1,000x bootstrapping for estimating the optimism corrected AUROC. RESULTS: Total 327 patients met inclusion criteria. The median (IQR) age and PSA density (PSAD) were 64 years (58-70) and 0.10 ng/mL2 (0.07-0.15), respectively. Biopsy history was as follows: 117 (36%) males were PBx-naive, 130 (40%) had previous negative PBx and 80 (24%) had previous positive PBx. The majority were White (65%); 6% of males self-reported Black. Overall, 44 (13%) patients were diagnosed with CSPCa on PBx. Black race, history of previous negative PBx and PSAD ≥0.15ng/mL2 were independent predictors for CSPCa on PBx and were included in the nomogram. The AUROC of the nomogram was 0.78 and the optimism corrected AUROC was 0.75. CONCLUSIONS: Our nomogram facilitates evaluating individual probability of CSPCa on PBx in males with PIRADS 1-2 mpMRI and may be used to identify those in whom PBx may be safely avoided. Black males have increased risk of CSPCa on PBx, even in the setting of PIRADS 1-2 mpMRI.

Artificial intelligence and urology: ethical considerations for urologists and patients.

The use of artificial intelligence (AI) in medicine and in urology specifically has increased over the past few years, during which time it has enabled optimization of patient workflow, increased diagnostic accuracy and enhanced computer analysis of radiological and pathological images. However, before further use of AI is undertaken, possible ethical issues need to be evaluated to improve understanding of this technology and to protect patients and providers. Possible ethical issues that require consideration when applying AI in clinical practice include patient safety, cybersecurity, transparency and interpretability of the data, inclusivity and equity, fostering responsibility and accountability, and the preservation of providers' decision-making and autonomy. Ethical principles for the application of AI to health care and in urology are proposed to guide urologists, patients and regulators to improve use of AI technologies and guide policy-making.

Radiomics Correlation to CD68+ Tumor-Associated Macrophages in Clear Cell Renal Cell Carcinoma.

INTRODUCTION: Renal cell carcinoma (RCC) is the ninth most common cancer worldwide, with clear cell RCC (ccRCC) being the most frequent histological subtype. The tumor immune microenvironment (TIME) of ccRCC is an important factor to guide treatment, but current assessments are tissue-based, which can be time-consuming and resource-intensive. In this study, we used radiomics extracted from clinically performed computed tomography (CT) as a noninvasive surrogate for CD68 tumor-associated macrophages (TAMs), a significant component of ccRCC TIME. METHODS: TAM population was measured by CD68+/PanCK+ ratio and tumor-TAM clustering was measured by normalized K function calculated from multiplex immunofluorescence (mIF). A total of 1,076 regions on mIF slides from 78 patients were included. Radiomic features were extracted from multiphase CT of the ccRCC tumor. Statistical machine learning models, including random forest, Adaptive Boosting, and ElasticNet, were used to predict TAM population and tumor-TAM clustering. RESULTS: The best models achieved an area under the ROC curve of 0.81 (95% CI: [0.69, 0.92]) for TAM population and 0.77 (95% CI: [0.66, 0.88]) for tumor-TAM clustering, respectively. CONCLUSION: Our study demonstrates the potential of using CT radiomics-derived imaging markers as a surrogate for assessment of TAM in ccRCC for real-time treatment response monitoring and patient selection for targeted therapies and immunotherapies.