Search Results (40)

Background/Objectives: Lymph node metastasis within the prostatic anterior fat pad (PAFP) is uncommon but may refine nodal staging when pelvic lymph node dissection and PSMA PET/CT are negative. Case Presentation: A 58-year-old man with PSA 59 ng/mL, negative digital rectal examination, and a PI-RADS 5 anterior lesion underwent transperineal MRI/US fusion biopsy, showing an acinar adenocarcinoma (Gleason score 5 + 5 = 10, ISUP grade group 5) confined to anterior cores. 18F-PSMA-1007 PET/CT showed intense intraprostatic uptake (SUVmax 55.2) without nodal or distant disease. Retropubic radical prostatectomy, bilateral extended pelvic lymph node dissection (ePLND), and separate PAFP submission were performed. Final pathology showed a 38 mm bilateral anterior tumor involving 35% of the prostate, focal anterior extraprostatic extension, negative margins, absent seminal vesicle and bladder neck invasion, perineural and lymphovascular invasion, and no cribriform or intraductal carcinoma. All 15 pelvic nodes were negative. One of two PAFP nodes contained a 3 mm PSA-positive metastasis without extranodal extension, resulting in pT3aN1 staging. Postoperative PSA persistence prompted radiotherapy plus androgen deprivation therapy; PSA was 0.01 ng/mL at 6 months. Conclusions: In very-high-risk anterior prostate cancer, separate PAFP evaluation may provide clinically relevant staging information when PSMA PET/CT and pelvic lymph nodes are negative. This case highlights the PAFP as a potential site of occult regional nodal disease. Full article

Whole-body dynamic positron emission tomography/computed tomography (WBD-PET/CT) has transformed medical imaging, enabling the fusion between (i) detailed anatomical maps of the human body and (ii) quantitative multi-parametric functional maps of specific biochemical and physiological processes across the human body beyond the semi-quantitative limitations of static PET/CT imaging. Latest developments in systems hardware, particularly with the introduction of long-axial-field-of-view (LAFOV) and Time-of-Flight (TOF) PET scanners and low-dose CT scanners, and in data analysis, primarily with direct parametric PET image reconstruction and Artificial Intelligence, offer unprecedented opportunities towards the wide clinical adoption of the superior quantitative accuracy and precision of WBD-PET/CT imaging overcoming current challenges, such as data acquisition complexity and long scan durations. This review aims to summarize the latest developments, current challenges, and emerging opportunities in WBD-PET/CT, emphasizing its potential to broaden the diagnostic and theranostic role of PET/CT in clinical practice. Full article

Multifunctional scaffolds that combine structural support with the controlled delivery of bioactive agents remain a major challenge in tissue engineering. To extend the use of these devices in biomedicine, 3D printing is presented as an alternative that enables the manufacture of complex devices tailored to each patient, thereby solving specific problems in a timely and efficient manner. In this study, porous 3D scaffolds were fabricated via digital light processing (DLP) using a PET-RAFT resin composed of 2-(dimethylamino)ethyl methacrylate (DMAEMA) and poly(ethylene glycol) diacrylate (PEGDA₅₇₅). Sodium chloride (NaCl) was incorporated as a porogen, while insulin-loaded poly(lactic-co-glycolic acid) (PLGA) nanoparticles were embedded as osteoinductive agents. The printed constructs exhibited high-resolution, reproducible trabecular-like architectures, as confirmed by micro-computed tomography (micro-CT), with interconnected pores averaging 70.7 ± 24.7 μm and a total porosity of 57.0 ± 6.98%. Thermal and chemical analyses confirmed scaffold stability and controlled degradability. Cytocompatibility assays using MC3T3-E1, C2C12, hGMSCs, and C166-GFP cells showed viability above 80% after 7 days (ISO 10993-5). Insulin-loaded nanoparticles enabled sustained release, characterized by an initial burst followed by gradual release up to 72 h. Dynamic bioreactor culture enhanced cell adhesion and RUNX2 expression, confirming the osteoinductive potential of the hybrid scaffold for advanced BTE applications. This study introduces an innovative PET-RAFT-derived resin that combines structural reinforcement with spatiotemporal regulation of insulin release, offering a potential strategy for enhanced biomaterial tissue engineering and tailored therapeutic interventions. Full article

Background: Lung cancer (LC) remains the leading cause of cancer-related mortality worldwide. Survival outcomes are strongly stage-dependent. Many patients are diagnosed at advanced stages due to pre-clinical and diagnostic delays. While advances in imaging, bronchoscopic techniques, molecular diagnostics, and systemic therapies have improved individualized treatment, system-level delays continue to limit their impact. Aim of the study: The aim of this narrative review is a synthesis with an implementation-oriented framework proposal. Part I synthesizes the peer-reviewed literature, Part II presents an operational framework integrating a Fast Trac Clinic (FTC) and a network of Lung Cancer Units (LCUs) including proposed turnaround-time (TAT) goals. Methods: A narrative review of the literature of selected European policy documents addressing diagnostic delays, rapid-access lung cancer pathways, and coordinated care models was conducted. Results: European models demonstrate that structured referral criteria, centralized coordination, and predefined interval targets can achieve the first specialist assessment within 7–10 days and the completion of diagnostics within 21–28 days in optimized settings. Key determinants of timeliness include: direct primary care referral, parallel diagnostic processes, prioritized pathology and molecular testing, and multidisciplinary team (MDT) assessment. We propose operational TAT targets for chest CT, PET-CT, histopathology, NGS, PFTs, and MDT decision-making. Conclusions: Reducing avoidable diagnostic and therapeutic delays in LC requires a coordinated, system-level approach. A standardized FTC-LCU pathway with explicit TAT benchmarks, multidisciplinary governance, and digital support infrastructure may improve diagnostic efficiency, increase the proportion of patients treated at earlier stages, and enhance patient experience. Prospective evaluation of implementation impact on stage distribution and survival is advised. Full article

Non-small cell lung cancer (NSCLC) remains the leading cause of cancer-related mortality globally. While multi-modal artificial intelligence (AI) models offer significant predictive potential, their translation into routine clinical practice is delayed by the “black box” nature of complex algorithms and the fragmentation of heterogeneous data. We present LANTERN-XGB, a hierarchical machine learning workflow designed to bridge this gap by generating interpretable “digital human avatars” for precision oncology. The methodology employs a multi-stage scalable tree boosting system (XGBoost) architecture utilizing shapley additive explanations (SHAP) for rigorous hierarchical feature selection, missing value management, and patient-specific decision support. The workflow was developed and benchmarked using a retrospective cohort of 437 patients with clinical N0 NSCLC, followed by validation on a prospective dataset (n = 100) and an independent external dataset (n = 100). The pipeline integrates diverse data modalities to predict occult lymph node metastasis (OLM). LANTERN-XGB identified a robust consensus signature driven by non-linear interactions among CT textural fragmentation, PET metabolic heterogeneity, tumor density distribution, and systemic clinical modulators. Exploratory transcriptomic pathway analysis (GSVA) revealed that high-risk predictions strongly correlate with systemic molecular dysregulation, such as the enrichment of immune-inflammatory signaling and metabolic stress pathways. The model achieved robust discrimination in external validation (AUC ≈ 0.77), performing comparably to state-of-the-art nomogram benchmarks. Crucially, the LANTERN-XGB framework demonstrated superior utility in handling diagnostic ambiguity; local force plots allowed for the correct reclassification of “borderline” prediction by visualizing feature interactions that standard linear models fail to capture. LANTERN-XGB provides a validated, open-source framework that successfully balances predictive power with clinical transparency. By empowering clinicians to visualize and verify the logic behind AI predictions, this workflow offers a pragmatic path for integrating reliable multi-modal avatars into daily medical decision-making. Full article

Background/Objectives: Robotic-assisted radical prostatectomy (RARP) is a standard treatment for localized and locally advanced prostate cancer; however, optimizing oncologic control while preserving urinary continence and erectile function remains challenging. Advances in preoperative imaging, molecular diagnostics, artificial intelligence (AI), and intraoperative assessment have the potential to refine surgical planning and execution. This review summarizes contemporary evidence on advanced imaging and intraoperative technologies used to optimize RARP outcomes. Methods: A narrative literature review was conducted of English-language studies published between 2015 and 2025 using PubMed/MEDLINE, Scopus, and Google Scholar. Studies evaluating multi-parametric and bi-parametric MRI, prostate-specific membrane antigen-based positron emission tomography/computed tomography (PSMA PET/CT), AI-assisted tumor modeling, and intraoperative histologic or molecular imaging techniques in the context of robotic-assisted radical prostatectomy were included. Evidence from randomized controlled trials, prospective and retrospective studies, technical feasibility reports, and expert consensus statements was reviewed. Results: MRI remains central to anatomic mapping and local staging but consistently underestimates true tumor extent, with implications for margin control. AI-assisted platforms improve tumor contouring accuracy and may meaningfully influence surgical decision-making. PSMA-based imaging enhances detection of extra-prostatic extension and nodal disease and shows early promise for ex vivo and intraoperative guidance. Intraoperative margin assessment techniques are supported by randomized evidence demonstrating improved functional outcomes without compromising short-term oncologic safety and emerging digital histologic technologies offer scalable alternatives for real-time margin evaluation. Conclusions: Integration of advanced anatomic, molecular, and intraoperative imaging technologies represents an evolving multimodal paradigm in RARP. Combined use of MRI, PSMA-based imaging, AI-assisted modeling, and rapid histologic assessment may enable more precise, individualized surgery that balances oncologic control with functional preservation. Further validation is required to define optimal implementation in routine clinical practice. Full article

Objective: We evaluate the performance and relevance of MRI to detect csPC in men with normal PSA. Methods: Out of our database of patients referred for prostate MRI, we selected men with PSA < 4 ng/mL for whom histopathology or at least 2 years of clinical follow-up data were available as standard of reference. Subgroup analyses were performed for the patients with PSA < 3 ng/mL, <2 ng/mL, and 2–3.9 ng/mL. The reasons for prostate MRI referral despite their normal PSA level were retrieved by exploring the patients’ files. The prostate MRIs were reported according to the Prostate Imaging and Reporting Data System (PI-RADS), and the overall assessment score was registered. For evaluation of the performance, PI-RADS ≥ 3 was set as a threshold for a positive exam. The patients without PC or only International Society of Urological Pathology (ISUP) grade group 1 PC (Gleason 3+3) were considered as one category having no csPC. The performance of prostate MRI was separately evaluated for detection of ISUP ≥ 2 and for ISUP ≥ 3 csPC. Results: A total of 148 men were included, with PSA ranging from 0.42 to 3.99 ng/mL (median 2.95, IQR 1.68–3.50) and age ranging from 36 to 84 years (median 58, IQR 52–66). A total of 74 men (50.0%) had a PSA level < 3 ng/mL, 42 (28.4%) had a PSA level < 2 ng/mL, and 106 (71.6%) had a PSA level of 2–3.9 ng/mL. They were referred for prostate MRI for a wide variety, and usually a combination of, reasons, such as younger age (<60 years in 55.4%, N = 82; <50 years in 17.6%, N = 26), abnormal digital rectal examination in 31.8% of cases (N = 47), suspicious PSA dynamics in 29.7% (N = 44), positive familial history in 27.0% (N = 40), clinical signs of prostatitis in 18.2% (N = 27), suspicious findings on Transrectal Ultrasound (TRUS) in 16.9% (N = 25), hematospermia in 7.4% (N = 11), hematuria in 4.1% (N = 6), incidental hot spot in the prostate on Fluoro-Deoxy-Glucose (FDG) Positron Emission Tomography (PET)–Computed Tomography (CT) in 4.1% (N = 6), lymphadenopathies on CT in 2.7% (N = 4), or severe patient anxiety in 3.4% (N = 5). Overall, ISUP ≥ 2 PC was present in 18.9% (N = 28) of cases, and MRI detected this with a sensitivity of 92.9%, a specificity of 66.7%, and a positive predictive value of 39.4%. ISUP ≥ 3 PC was present in 9.5% (N = 14) of cases, and prostate MRI detected this with a sensitivity of 100%, a specificity of 61.2%, and a positive predictive value of 21.2%. In patients with PSA < 2 ng/mL (N = 42), no csPC was found, but MRI generated false positives in 33.3%. Conclusions: Performing prostate MRI in men with normal PSA (<4 ng/mL) seems useful if there are other reasons that increase the clinical suspicion of csPC. In about one-fifth of these patients, csPC is present and MRI has high sensitivity for its detection. Prostate MRI has, however, low positive predictive value in this patient group, and clinicians should be aware of the risk of false-positive MRI. Below a PSA level of 2 ng/mL, no csPC was found and prostate MRI generated only false positives, suggesting limited value in this subgroup. Full article

Objective: We present the first clinical experience with the BIOGRAPH One next-generation PET/MRI system scanner, evaluating its performance for body and brain imaging in patients across multiple tracers. Methods: A total of 59 patients were scanned on the BIOGRAPH One PET/MRI following standard clinical PET/CT (n = 52) or first-generation PET/MRI (Biograph mMR, n = 7). Scans comprised 30 total body (TB), whole body (WB), or regional scans with [¹⁸F]FDG, and 29 brain scans with either [¹⁸F]FDG (n = 5), [¹⁸F]FE-PE2I (n = 10), [¹⁸F]FET (n = 4), or [⁶⁸Ga]Ga-DOTATOC (n = 10). The PET image quality was visually assessed using a 5-point Likert scale (1 = very good to 5 = very bad) and compared with clinical scans acquired on either a current-generation digital PET/CT or a first-generation PET/MRI system, including evaluation of diagnostic concordance. PET quantification and image noise was compared in brain and WB/TB [¹⁸F]FDG PET scans. Results: PET image quality was rated as good or very good in 93% of scans with a median [inter-quartile range] score of 1.5 [1.5;2]. In 99% of cases, image quality was judged equal to or better than the clinical reference scan (median score 3 [2.5;3]). Diagnostic concordance was observed in 99% of readings. Imaging metrics revealed the anticipated regional bias in brain imaging, while no significant bias was observed in body imaging. Image noise was comparable to that observed with digital PET/CT and demonstrated superiority over first-generation PET/MRI despite potential degradation related to isotope decay in BIOGRAPH One PET/MRI acquisitions scans performed at the end of the imaging workflow. Conclusions: Within the study limitations related to sequential imaging, the BIOGRAPH One PET/MRI scanner demonstrated improved PET sensitivity and workflow potential over its first-generation predecessor, which may allow for broader clinical and research applications. Full article

Background: Diffuse large B-cell lymphoma (DLBCL) is a biologically heterogeneous malignancy, with various outcomes despite significant advances in therapeutic options. Current conventional prognostic tools, e.g., the International Prognostic Index (IPI), lack sufficient precision at an individual patient level. However, artificial intelligence (AI), including machine learning (ML) and deep learning (DL), can enable specialists to navigate complex datasets, with the final aim of improving prognostic models for DLBCL. Objectives: This scoping review aims to systematically map the current literature regarding the use of AI/ML techniques in DLBCL outcome prediction and risk stratification. We categorized studies by data modality and computational approach to identify key trends, knowledge gaps, and opportunities for their translation into current practice. Methods: We conducted a structured search of the PubMed/MEDLINE, Scopus, and Cochrane Library databases through July 2025 using terms related to DLBCL, prognosis, and AI/ML. Eligible studies included original papers applying AI/ML to predict survival outcomes, classify risk groups, or identify prognostic subtypes. Studies were categorized based on input modality: clinical, positron emission tomography/computed tomography (PET/CT) imaging, histopathology, transcriptomics, genomics, circulating tumor DNA (ctDNA), and multi-omics data. Narrative synthesis was performed in line with PRISMA-ScR guidelines. Results: From the 215 records screened, 91 studies met the inclusion criteria. Group-wise we report the following categories: clinical risk features (n = 8), PET/CT imaging (n = 30), CT (n = 1), digital pathology (n = 3), conventional histopathology (n = 2), gene expression profiling (n = 19), specific mutational signatures (n = 18), ctDNA (n = 3), microRNA (n = 2), and multi-omics integration (n = 5). The most common techniques reported amongst the papers included ensemble learning, convolutional neural networks (CNNs), and LASSO-based Cox models. Several AI techniques demonstrated superior predictive performance over IPI, with area under the curve (AUC) values frequently exceeding 0.80. Multi-omics models and ctDNA-based predictors showed strong potential for clinical translation, a perspective worth considering in further studies. Conclusions: AI/ML methods are increasingly used in DLBCL to improve prognostic accuracy by leveraging data types with diverse inputs. These approaches allow an enhanced stratification, superior to traditional indices, and support the early identification of high-risk patients, earlier guidance for therapy tailoring, and early trial enrollment for flagged cases. Future investigations should focus on external validation and improvement of model interpretability, with tangible perspectives of integration into real-world workflows and translation from bench to bedside. Full article

We aimed to establish non-invasive diagnostic models comparable to pathology testing and explore reliable digital imaging biomarkers to classify diffuse large B-cell lymphoma (DLBCL) and invasive ductal carcinoma (IDC). Our study enrolled 386 breast nodules from 279 patients with DLBCL and IDC, which were pathologically confirmed and underwent ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography/computed tomography (PET/CT) examination. Patients from two centers were separated into internal and external cohorts. Notably, we introduced 2.5D deep learning and machine learning to extract features, develop models, and discover biomarkers. Performances were assessed using the area under curve (AUC) and confusion matrix. Additionally, the Shapley additive explanation (SHAP) and local interpretable model-agnostic explanations (LIME) techniques were employed to interpret the model. On the internal cohort, the optimal model PT_TDC_SVM achieved an accuracy of 0.980 (95% confidence interval (CI): 0.957–0.991) and an AUC of 0.992 (95% CI: 0.946–0.998), surpassing the other models. On the external cohort, the accuracy was 0.975 (95% CI: 0.913–0.993) and the AUC was 0.996 (95% CI: 0.972–0.999). The optimal imaging biomarker PET_LBP-2D_gldm_DependenceEntropy demonstrated an average accuracy of 0.923/0.937 on internal/external testing. Our study presented an innovative automated model for DLBCL and IDC, identifying reliable digital imaging biomarkers with significant potential. Full article

Background: Despite its central role in pediatric pre-surgical evaluation of drug-resistant focal epilepsy, conventional analog ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) PET/CT (aPET) systems often yield modest epileptogenic zone (EZ) detection rates (~50–60%). Silicon photomultiplier–based digital PET/CT (dPET) promises enhanced image quality, but its performance in pediatric epilepsy remains untested. Methods: We retrospectively analyzed 22 children (mean age 11.5 ± 2.6 years) who underwent interictal brain ¹⁸F-FDG PET/CT: 11 on an analog system (Discovery ST, 2018–2019) and 11 on a digital system (Biograph Vision 450, 2020–2021). Three blinded nuclear medicine physicians independently scored EZ localization and image quality (4-point scale); post-surgical histology and ≥1-year clinical follow-up served as reference. Results: The EZ was correctly identified in 8/11 analog scans (72.7%) versus 10/11 digital scans (90.9%). Average image quality was significantly higher with dPET (3.0 ± 0.9 vs. 2.1 ± 0.9; p < 0.05), and inter-reader agreement improved from good (ICC = 0.63) to excellent (ICC = 0.91). Conclusions: Our preliminary findings suggest that dPET enhances image clarity and reader consistency, potentially improving localization accuracy in pediatric epilepsy presurgical workups. Full article

This study assesses the clinical deployment of SubtlePET™, a commercial AI-based denoising algorithm, across three radiotracers—¹⁸F-FDG, ⁶⁸Ga-PSMA-11, and ¹⁸F-FDOPA—with the goal of improving image quality while reducing injected activity, technologist radiation exposure, and scan time. A retrospective analysis on a digital PET/CT system showed that SubtlePET™ enabled dose reductions exceeding 33% and time savings of over 25%. AI-enhanced images were rated interpretable in 100% of cases versus 65% for standard low-dose reconstructions. Notably, 85% of AI-enhanced scans received the maximum Likert quality score (5/5), indicating excellent diagnostic confidence and noise suppression, compared to only 50% with conventional reconstruction. The quantitative image quality improved significantly across all tracers, with SNR and CNR gains of 50–70%. Radiotracer dose reductions were particularly substantial in low-BMI patients (up to 41% for FDG), and the technologist exposure decreased for high-exposure roles. The daily patient throughput increased by an average of 4.84 cases. These findings support the robust integration of SubtlePET™ into routine clinical PET practice, offering improved efficiency, safety, and image quality without compromising lesion detectability. Full article

Background/Objectives: Pulmonary lymphangitic carcinomatosis (PLC) is a rare, aggressive manifestation of metastatic cancer characterized by lymphatic infiltration of the lungs, typically indicating advanced disease and poor prognosis. Methods: This comprehensive narrative review evaluates the role of [18F]fluorodeoxyglucose ([18F]FDG) positron emission tomography (PET) imaging in assessing PLC. Results: Current evidence demonstrates that [18F]FDG PET/CT achieves high diagnostic accuracy, with sensitivity and specificity ranging from 86 to 97% and 84 to 100%, respectively, particularly when employing semiquantitative metrics such as peritumoral standardized uptake value (SUVmax) thresholds (e.g., ≥2.1). PET/CT surpasses high-resolution computed tomography (HRCT) in distinguishing PLC from mimics like pulmonary sarcoidosis by identifying distinct metabolic patterns: bronchovascular hypermetabolism in PLC versus subpleural nodular uptake in sarcoidosis. Prognostically, metabolic tumor burden (e.g., SUVmax × involved lobes) and novel cPLC classifications (localized to the ipsilateral or contralateral lung) independently predict progression-free survival. However, challenges persist, including non-specific tracer uptake in inflammatory conditions and variability in SUV measurements due to technical factors. Emerging digital PET/CT systems, with enhanced spatial resolution, may improve the detection of focal PLC and reduce false negatives. While [18F]FDG PET/CT is invaluable for whole-body staging, therapeutic monitoring and biopsy guidance, the standardization of protocols and multicenter validation of prognostic models are critical for clinical integration. Future research should explore novel tracers (e.g., PSMA for prostate cancer-related PLC) and machine learning approaches to refine diagnostic and prognostic accuracy. Conclusions: This review underscores the role and the transformative potential of [18F]FDG PET/CT in PLC management while advocating for rigorous standardization to maximize its clinical utility. Full article

Background: The optimal diagnostic and therapeutic strategies for prostate cancer (PCa) in patients aged ≥75 years (mild-old and oldest-old) are still contentious. Resource allocation and ideal treatment for older patients are challenges, mainly due to their comorbidities and reduced life expectancy. This survey aims to assess current clinical practices and the experiences of healthcare providers in the diagnosis and management of elderly patients with PCa. Materials and Methods: In Northeast Italy, members of the Gruppo Uro-Oncologico del Nord-Est (GUONE) conducted a survey involving 104 physicians of different specialties (Nuclear Medicine, Medical Oncology, Radiation Oncology, Radiology, Urology) between 1 November 2024 and 30 November 2024. The survey encompassed 51 questions, evaluating various diagnostic and therapeutic scenarios. Results: Digital rectal exam (DRE) was recommended by 35.9% of physicians for patients aged 75 or older at risk of PCa. PSA testing was continued in 76.3% of these patients. For 36.5% of the physicians, there should be no age limit for prostate biopsy. Moreover, 42.6% of physicians recommended a magnetic resonance imaging (MRI)-guided prostate biopsy regardless of age. A prostate biopsy was deemed mandatory before initiating any form of hormonal therapy by 57.7% of the participants. For 22.3% and 34.7% of physicians, there should be no age limit for prostate MRI and PET/CT for staging purposes. Interestingly, PET/CT was not recommended in 52% of cases as a staging tool for patients older than 85 years. For patients without comorbidities, the age limit to consider radical prostatectomy (RP) was 75, with 58.6% of physicians in favor. There were no definitive limits for radiotherapy (RT). Chemotherapy had an age limit for 81.6% of the respondents; for 18.4%, 22.5%, and 26.5% of physicians, age limits were 75, 80, and 85 years, respectively. The use of androgen receptor pathway inhibitors (ARPIs) had no definitive age limits for 46.5% of respondents. For patients with no comorbidities and low-volume metastatic PCa, the preferred option was androgen deprivation therapy + ARPIs + RT. The follow-up schedule after RP or RT exhibited heterogeneity with no consensus regarding the frequency of PSA testing or the age at which it should be discontinued. Conclusions: This survey highlights the need for consensus guidelines in diagnosing and managing mild-old and oldest-old elderly PCa patients. With the aging population, standardized protocols are essential to ensure optimal care. Full article

Background/Objectives: The purpose of this study was to develop the gemcitabine-loaded drug-eluting beads (G-DEBs) for transarterial chemoembolization (TACE) in rabbit renal tumors and to evaluate their antitumor effect using 2-deoxy-2-[(18)F]fluoro-D-glucose positron emission tomography/X-ray computed tomography (¹⁸F-FDG PET/CT). Methods: DEBs were prepared by polyvinyl alcohol-based macromer crosslinked with N-acryl tyrosine and N,N′-methylenebis(acrylamide). Gemcitabine was loaded through ion change to obtain G-DEBs. Their particle size and drug release profile were characterized. VX2 tumors were implanted in the right kidney of rabbits to establish the renal tumor model. The tumor-bearing rabbits received pre-scan by ¹⁸F-FDG PET/CT, followed by targeted transarterial injection of G-DEBs under digital subtraction angiography (DSA) guidance. The rabbits received another ¹⁸F-FDG PET/CT scan 10 or 14 days after the treatment. The therapeutic effect was further validated by histopathological analysis of the dissected tumors. Results: The average particle size of the microspheres was 58.06 ± 0.50 µm, and the polydisperse index was 0.26 ± 0.002. The maximum loading rate of G-DEBs was 18.09 ± 0.35%, with almost 100% encapsulation efficiency. Within 24 h, GEM was eluted from G-DEBs rapidly and completely, and more than 20% was released in different media. DSA illustrated that G-DEBs were delivered to rabbit renal tumors. Compared with the untreated control group with increased tumor volume and intense ¹⁸F -FDG uptake, the G-DEBs group showed significant reductions in tumor volume and maximum standard uptake value (SUV_max) 10 or 14 days after the treatment. Histopathological analysis confirmed that the proliferating area of tumor cells was significantly reduced in the G-DEBs group. Conclusions: Our results demonstrated that G-DEBs are effective in TACE treatment of rabbit VX2 renal tumors, and ¹⁸F-FDG PET/CT provides a non-invasive imaging modality to monitor the antitumor effects of TACE in renal tumors. Full article