Search Results (1,042)

Background/Objectives: Although the Spinal Instability Neoplastic Score (SINS) is widely used to estimate spinal metastases fracture risk and guide decisions on stabilisation procedures, prior studies have demonstrated mixed results. Patients with the same score exhibit clinically heterogeneous outcomes, with some SINS criteria correlating less well with the estimated fracture risk than others. There are also barriers to implementation such as the time burden required for manual calculation and interobserver variability associated with qualitative morphological criteria. SINS also lacks sensitivity for detecting latent structural compromise in treatment-naive patients and those susceptible to the iatrogenic effects of stereotactic body radiation therapy. This review aims to evaluate emerging imaging, biomechanical, and microstructural markers with the potential to improve fracture risk stratification and prognostication for spinal oncology patients. Methods: We synthesise evidence across three innovative frontiers: (1) biomechanical modelling, including CT-derived finite element analysis and failure-load pattern models; (2) radiomics, utilizing radiomics features from radiological imaging to develop a predictive model; and (3) microstructural MRI biomarkers, exploring the translatability of the Vertebral Bone Quality score, fat fraction, and paraspinal muscle atrophy from osteoporosis to the metastatic spine. Results: Emerging biomechanical, radiomic and microstructural imaging markers show potential in addressing some limitations of traditional SINS criteria for fracture risk stratification across the spinal oncology treatment continuum, from initial diagnosis to post-radiation surveillance, thereby facilitating more precise risk assessment. However, current evidence remains largely retrospective and heterogeneous, and further validation is required before clinical adoption. Conclusions: We propose a framework that shifts the paradigm from conventional morphological scoring toward a multiparametric assessment of spinal stability. Full article

Background: Breast cancer (BC) remains one of the leading causes of cancer-related deaths worldwide, with early detection being essential for improving survival rates, treatment outcomes, and preventive women’s healthcare strategies. Artificial Intelligence (AI), particularly deep learning (DL) and machine learning (ML) algorithms, has emerged as a promising tool for improving the accuracy and efficiency of BC diagnosis. This systematic review explores the role of AI in early BC detection and its implications for preventive and patient-centered women’s healthcare. Methods: A comprehensive search was conducted in PubMed and Scopus for studies published between January 2015 and December 2025, following PRISMA guidelines. The search strategy included combinations of MeSH terms and free-text keywords related to artificial intelligence, machine learning, deep learning, BC screening, mammography, magnetic resonance imaging (MRI), ultrasound, and BC detection. Eleven studies involving approximately 148,170 participants were included. Methodological quality was assessed according to study design. Results: AI-driven diagnostic systems demonstrated improved accuracy, sensitivity, specificity, and efficiency compared with conventional approaches. AI applications in mammography and ultrasound reduced radiologists’ workload and healthcare costs while enhancing cancer detection rates, particularly in women with high breast density. AI models also showed potential in identifying metastases and predicting clinical outcomes, supporting more efficient patient management and follow-up care. Conclusions: AI-based tools represent a promising advancement in BC detection and screening efficiency. Their integration into BC screening programs may strengthen preventive women’s healthcare services and improve patient outcomes. However, further large-scale clinical validation and real-world implementation studies are required before widespread clinical implementation. Full article

Background: Oligometastatic non-small cell lung cancer (OMD NSCLC) represents a distinct clinical state with limited metastatic spread, where local ablative therapies (LAT) combined with systemic treatment may improve outcomes. Accurate staging and prognostic assessment are critical, with ¹⁸F-FDG PET/CT emerging as a valuable tool for detecting metabolically active tumor burden. Results: We retrospectively analyzed 38 patients with synchronous OMD NSCLC who received radiotherapy. All patients underwent ¹⁸F-PET/CT and brain imaging for staging. Semi-quantitative ¹⁸F-PET/CT parameters, including metabolic tumor volume (MTV) and total lesion glycolysis (TLG) of primary tumor and metastatic lesions, were measured and associated with progression-free survival (PFS) and overall survival (OS) using Cox proportional hazard models. The median PFS and OS were 8.28 and 21.62 months, respectively. Higher MTV and TLG values of metastases were significantly associated with shorter PFS and OS (p < 0.01). In multivariable analysis, TLG of metastases above the median remained an independent predictor of worse PFS (HR = 2.78, p = 0.031) and OS (HR = 3.12, p = 0.024), alongside clinical factors such as ECOG performance status 2 and having multiple metastases. The metabolic parameters of the primary tumor did not predict survival outcomes. Conclusions:¹⁸F-PET/CT-derived metabolic parameters, particularly the TLG of metastatic lesions, may provide significant prognostic information in oligometastatic NSCLC beyond clinical variables. These findings may support the integration of ¹⁸F-PET/CT metrics for future trials involving patients treated with LAT in oligometastatic NSCLC. Full article

Background: Brain metastases are the most common intracranial tumors in adults and are traditionally considered well-demarcated lesions amenable to complete surgical resection. Nonetheless, increasing histopathological evidence demonstrates that metastatic cells may infiltrate beyond the contrast-enhancing margin into surrounding brain parenchyma, challenging the reliability of conventional imaging for defining true tumor boundaries. Confocal laser endomicroscopy (CLE) using Sodium Fluorescein (SF) has emerged as a novel intraoperative imaging modality capable of providing real-time, high-resolution optical biopsies, potentially improving margin assessment during metastasis surgery. Methods: A systematic literature search was performed according to PRISMA guidelines across PubMed, Embase, Scopus, Cochrane Library, and Google Scholar up to 3 March 2026. Studies evaluating intraoperative CLE with SF in adult patients with brain metastases were included. Data regarding study design, patient population, CLE system, imaging characteristics, and diagnostic performance were extracted. Risk of bias was assessed using the QUADAS-2 tool. Results: Ten studies met the inclusion criteria for qualitative synthesis, comprising over 650 patients; however, most studies included heterogeneous intracranial tumor populations, with only a subset specifically involving brain metastases. CLE enabled real-time visualization of tumor microarchitecture and demonstrated high sensitivity for tumor detection, frequently exceeding 90% in prospective studies. Specificity varied across studies, reflecting challenges in distinguishing tumor infiltration from reactive tissue at the tumor–brain interface. The MetInfilt trial highlighted that infiltrative growth patterns are common in brain metastases and can be visualized intraoperatively using CLE. Additional studies demonstrated that fluorescein-based CLE allows differentiation of tumor zones and may facilitate targeted margin assessment; however, evidence demonstrating improvement in clinically meaningful outcomes such as extent of resection, local recurrence, progression-free survival, or overall survival remains limited. Conclusions: Confocal laser endomicroscopy using SF represents a promising intraoperative adjunct for assessing tumor margins in brain metastasis surgery. By enabling real-time microscopic visualization of the metastasis–brain interface, CLE may support a more biologically informed surgical strategy. Full article

In this review, we explore the evolving role of endoscopic ultrasound (EUS) in diagnosing and managing pancretobiliary malignancies. For solid pancreatic lesions, techniques like fine-needle biopsy (FNB), contrast-enhanced EUS (CE-EUS), and macroscopic on-site evaluation (MOSE) improve sample quality and diagnostic accuracy. In cystic pancreatic lesions, fine-needle aspiration (FNA), molecular testing, and confocal laser endomicroscopy (nCLE) aid in distinguishing benign from malignant cysts. For cholangiocarcinoma, EUS guided sampling is more accurate than CT in assessing distal lesions and lymph node metastases, while combining EUS with magnetic resonance cholangiography (MRC) enhances diagnostic sensitivity. In gallbladder cancer, EUS surpasses CT and MRI in detecting lymphadenopathy and staging tumors. EUS-FNB (Fine needle biopsy) improves biopsy accuracy, especially for unresectable cases. These advancements highlight EUS as a critical tool for early cancer detection, staging, and tissue acquisition. Beyond diagnosis, EUS plays a pivotal therapeutic role in managing complications such as malignant biliary obstruction and gastric outlet obstruction, offering minimally invasive alternatives like EUS-guided biliary drainage and gastroenterostomy with high clinical success and improved patient outcomes. Full article

Background: Reliable assessment of cervical lymph node metastases remains a key challenge in the management of oral squamous cell carcinoma (OSCC). While elective ipsilateral neck dissection (ND) is widely accepted, the benefit of contralateral ND and the influence of tumor site on metastatic risk remain incompletely defined. This study aimed to evaluate patterns of lymphatic metastases, the diagnostic accuracy of preoperative staging, and the therapeutic relevance of ipsilateral and contralateral ND. Methods: A retrospective single-center cohort study was conducted including 287 patients with histologically confirmed OSCC treated between 2013 and 2019. Patterns of lymph node metastases were analyzed with respect to tumor localization and clinicopathological factors. Multivariate binary logistic regression was performed to identify predictors of cervical lymph node metastases. The diagnostic accuracy of preoperative staging was evaluated using histopathological findings as the reference standard. Results: Tumor localization and histopathological grading significantly influenced the occurrence of lymph node metastases. OSCC of the maxilla demonstrated a significantly lower observed rate of cervical and occult metastases compared with other tumor sites. Occult metastases were detected in 16.9% of primary tumor cases, with only two contralateral occult metastases observed. The calculated number needed to treat (NNT) was 6 for ipsilateral elective ND and 74 for contralateral elective ND. Preoperative staging showed limited diagnostic accuracy, with a negative predictive value of 0.83 and a positive predictive value of 0.65. Conclusions: Elective ipsilateral ND remains an essential component in the surgical management of OSCC due to the considerable rate of occult metastases and the limited reliability of preoperative staging. In contrast, the benefit of contralateral elective ND appears limited in patients without midline-crossing tumors. Maxillary OSCC and well-differentiated tumors demonstrated a significantly lower metastatic risk, supporting a more individualized risk-adapted approach to neck dissection in selected cases. Full article

This study aims to evaluate the quantitative impact of FDG-PET on detecting extra-pelvic metastases in women with cervical cancer, using population-based data, following its approval by US Medicare/Medicaid in 2005 for staging patients without detectable extra-pelvic metastases on CT or MRI scans. Surveillance, Epidemiology, and End Results (SEER) data from eight US registries from 1975 to 2021 were analyzed. The proportions of synchronous metastases “Synchronous/(Synchronous + Metachronous)” were compared between the pre-PET era (1995–1999 and 2000–2004) and the PET era (2010–2014). The estimated fraction of extra-pelvic metastases at initial diagnosis was 35% in the pre-PET era (2000–2004) compared to 46% in the PET era (2010–2014) (absolute difference 11%; p < 0.001). The proportion of undetected metastases decreased from 65% to 54%, indicating that PET identified up to 17% (i.e., [65 − 54]/65) of previously undetectable subclinical metastases. Likewise, the comparison of data from 1995–1999 vs. 2010–2014 showed 29% vs. 46% (absolute difference 17%; p <0.001). The proportion of undetected metastases decreased from 71% to 54%, suggesting that PET identified up to 24% (i.e., [71 − 54]/71) of the previously undetectable subclinical extra-pelvic metastases. In conclusion, up to ≈17–24% of subclinical extra-pelvic metastases, previously undetectable at initial diagnosis, appear to be identified through PET, findings that are consistent with and externally validate our prior population-based observations in non-small cell lung cancer. Full article

Accurate regional lymph node staging is essential for guiding treatment and predicting outcomes in non-small cell lung cancer. While the 9th edition of the TNM classification introduced prognostic subdivisions for N2 disease, the N1 category remains a single, unified descriptor. However, N1 disease is highly heterogeneous. Evidence shows significant survival differences between single-station (N1a) and multi-station (N1b) involvement, as well as between peripheral (N1p) and hilar (N1h) metastases. Standard medical imaging evaluation and conventional bronchoscopy often fail to detect “occult N1 disease,” leading to postoperative stage migration and suboptimal treatment sequencing. This diagnostic gap affects critical clinical decisions, including the selection of patients for sublobar resection, the administration of neoadjuvant chemoimmunotherapy, and the precision of radiation target volumes. The main obstacle to refining N1 staging has been the limited ability of existing clinical staging modalities to access and accurately assess N1p nodes. However, recent technological advances, particularly in thin convex probe endobronchial ultrasound examination, have renewed interest in bronchoscopic evaluation of N1p and in improving preoperative clinical N1 staging. The purpose of this review is to summarize the biological and immunological basis for N1 subclassification and evaluate how emerging technologies can bridge the gap between clinical and pathological staging. Refining the N1 compartment is vital for a personalized staging system that reflects the true biological spectrum of lung cancer. Full article

Background: The molecular concordance between primary lung adenocarcinoma and metastatic lesions remains incompletely characterized despite its direct implications for precision oncology and biopsy-driven therapeutic decision-making. This prospective monocentric paired-sample study evaluated genomic concordance between primary lung adenocarcinoma and synchronous thoracic metastatic lesions using targeted next-generation sequencing (NGS). Methods: We identified 27 treatment-naïve patients with histologically confirmed lung adenocarcinoma who underwent paired molecular profiling of the primary tumor and a synchronous thoracic metastatic site (pleural or intrapulmonary). DNA and RNA were analyzed using validated institutional NGS platforms. Genomic alterations, including clinically actionable oncogenic drivers consistently covered by the sequencing panel used in each pair, were compared across matched samples. Concordance was assessed using exact binomial confidence intervals, Cohen’s κ statistics, McNemar tests, and paired Wilcoxon signed-rank tests. Results: Actionable driver alterations were identified in 17 of 27 patients (63.0%; 95% CI 42.4–80.6), including EGFR mutations (40.7%), KRAS alterations (18.5%), and one ALK gene rearrangement (3.7%). TP53 concurrent mutations were detected in 14 cases (51.9%). Across all 27 paired samples, driver-level concordance was 100% (95% CI 87.2–100), with perfect agreement for EGFR, KRAS, and ALK alterations (κ = 1.00). TP53 mutations showed high concordance (92.9%; κ = 0.85), while CNVs were concordant in 88.0% of evaluable pairs. Variant allele frequency (VAF) comparisons, adjusted for tumor cellularity, further supported the apparent clonal stability of driver alterations across paired samples. Conclusions: This study demonstrates very high molecular concordance between primary lung adenocarcinomas and their synchronous pleural or intrapulmonary metastases. The observed 100% concordance of actionable driver alterations across paired specimens supports the clinical reliability of thoracic metastatic biopsies for baseline molecular profiling in treatment-naïve disease. Although limited by sample size, these findings support the biological stability of actionable driver alterations during early thoracic metastatic dissemination. Full article

Detecting brain tumors can be challenging as a clinical problem because of tumor heterogeneity and reliance on manual neuroimaging interpretation, which can be prone to human error. Artificial intelligence (AI) has shown strong potential as a clinical decision-support tool, assisting radiologists in improving diagnostic accuracy and supporting the interpretation of neuroimaging data. AI using machine learning (ML) and deep learning (DL) algorithms has performed credibly in tumor detection, segmentation, and classification tasks. Challenges such as dataset bias, limited generalization, lack of explainability, and high computational costs must be addressed before clinical application. This article provides a comprehensive review of AI methods applied to brain tumor imaging, with a primary focus on adult diffuse gliomas and secondary coverage of brain metastases, meningiomas, and pediatric tumors where relevant. The major contribution of this review is a new three-factor (diagnostic tasks, learning strategies, and data modalities) taxonomy. Beyond accuracy-based metrics, we provide a qualitative assessment of robustness, generalization, and the principal barriers to clinical adoption identified in the published literature, while acknowledging that comprehensive clinical utility evidence remains an open research direction. Full article

Background: Understanding lymph node involvement in head and neck cancers is crucial for developing effective treatment strategies and improving patient outcomes. Accurate identification of nodal metastases can enhance prognostic assessment, improve survival rates, and reduce the risk of recurrence. This study aimed to evaluate the association of lymph node metastases with primary tumor characteristics, with a particular focus on tumor stage and primary tumor location in head and neck squamous cell carcinoma (HNSCC). Methods: The study included 170 patients diagnosed with HNSCC at a single medical center between 2022 and 2025. Clinical and pathological assessments of the size and extent of primary tumors were performed according to the American Joint Committee on Cancer TNM classification, version 8. Results: The study cohort consisted of adult patients with a mean age of 61.9 years, of whom 40.6% were female. The tongue was the most common primary tumor site (54.7%), followed by the floor of the mouth (22.4%) and the jaw (8.8%). Clinical staging identified lymph node metastases (cN1 or higher) in 32.4% of patients, whereas pathological evaluation revealed nodal involvement in 38.9%. A statistically significant association was observed between tumor stage and the presence of lymph node metastases (p < 0.001). Additionally, the frequency of nodal metastases varied by anatomical site, with the highest rates observed in tumors of the floor of the mouth and the tongue. Conclusions: These findings suggest that both tumor stage and primary tumor location are associated with an increased risk of lymph node metastases. The results underscore the limitations of clinical staging in detecting nodal disease and highlight the prognostic significance of tumor stage and anatomical site in assessing metastatic risk. Full article

Background and Clinical Significance: Lymph node metastases from carcinoma of unknown primary origin (CUP) are a rare and diagnostically challenging entity, particularly when arising from thoracic malignancies with atypical clinical presentations. This study aims to illustrate the essential nature of multidisciplinary integration, with a particular emphasis on the role of the pathologist in identifying occult thoracic tumors. Case Presentation: We report three cases of patients presenting with cervical or systemic lymphadenopathy as the initial clinical manifestation. Comprehensive diagnostic workups included advanced imaging (CT, MRI, and PET), comprehensive histopathological analysis, and next-generation sequencing of circulating tumor DNA. Case one and case two were diagnosed as occult primary non-mucinous lung adenocarcinomas, based on the integration of morphological features and immunohistochemical co-expression of TTF-1 and Napsin A, despite the absence of identifiable lung lesions. One case harbored an ALK rearrangement, guiding effective targeted therapy with alectinib. Case three involved metastatic pleural epithelioid mesothelioma, which presented with systemic lymphadenopathy and was initially misclassified as metastatic adenocarcinoma. Diagnosis was confirmed by the loss of BAP1 expression by immunohistochemistry and the detection of a BAP1 S160fs*1 mutation, emphasizing the role of molecular pathology. Conclusions: Lymphadenopathy as the first manifestation of thoracic malignancy is a rare but clinically significant occurrence. In such atypical presentations, pathologists play a pivotal role in diagnosis, often leading the process when clinical or radiological clues are minimal or absent. Accurate histopathological assessment is essential to establish a correct diagnosis and guide appropriate therapy. A multidisciplinary approach remains the cornerstone of diagnostic precision in CUP cases. Full article

Background/Objectives: Small-cell prostate cancer (SCPC) is a rare, aggressive variant of prostate cancer with poor prognosis, arising “de novo” or through lineage plasticity from conventional adenocarcinoma under androgen receptor-targeted therapies. Characterized by low PSA levels despite high tumor burden and visceral metastases, SCPC poses diagnostic challenges with conventional and PSMA-targeted imaging due to variable tracer uptake. This narrative review aims to evaluate the role of PET/CT tracers in clinical and preclinical settings for SCPC diagnosis, staging, and management. Methods: A systematic literature search was conducted on PubMed and Scopus up to December 2025 using terms “PET OR positron emission tomography AND prostate OR prostatic AND small-cell NOT non-small-cell”. Eight studies (five clinical, three preclinical) on the role of PET/CT imaging in SCPC were included and analyzed for study design, population, tracers, and findings, with comparative evaluation of diagnostic performance across PET tracers. Results: Clinical studies showed that ¹¹C-choline detects progression at low PSA but misses SCPC; ¹⁸F-FDG exhibited a high SUVmax value for distinguishing SCPC from adenocarcinomas with neuroendocrine differentiation, predicting poor survival; ⁶⁸Ga-DOTATATE identified NEPC/SCPC with promising prognostic/therapeutic value for selected cases. Preclinical models evaluated ⁸⁹Zr-tracers targeting DLL3 or CDCP1 (an antigen expressed in aggressive neuroendocrine tumours) and ¹⁸F-BnTP (a target of mitochondrial activity) in SCPC subtypes, focusing on translational imaging. Conclusions: From this review, although still based on limited literature evidence and mostly derived from retrospective and small SCPC sub-cohorts,¹⁸F-FDG PET/CT currently appears as the most reliable tracer for SCPC, aiding tumor detection and prognostication when PSMA/choline imaging fails. In the preclinical setting, DLL3/CDCP1-targeted agents emerge as promising theranostics tools. Multimodal imaging approach and prospective trials are needed for standardization and patient-based SCPC management. Full article

Background/Objectives: Metastatic Prostate Cancer (mPCa) is generally treated with systemic therapy. Many of these treatments, particularly androgen ablation, are not curative and cause substantial morbidity. Oligometastasis is defined as a limited number of metastatic deposits, whose disease does not seem to progress to a widespread distribution of cancer. There have been some reports of trials of localized treatment of PCa oligometastatic disease with curative intent. We herein report a case of oligometastatic prostate cancer treated primarily with surgical removal of metastases, which has no evidence of active disease twenty years post-operatively. Methods: Extensive retrospective chart review, immunohistochemical staining, growth rate calculations, and imaging studies were performed to trace the progression of this patient’s disease course. Results: A detailed investigation of biochemical markers of recurrence revealed normal-low prostate specific antigen (PSA) despite advanced disease, early rather than metachronous dissemination of metastases to distant sites, and hypoxia-conditioned phenotypic plasticity and memory in disseminated tumor cells (DTCs). Conclusions: This rare outlier case of oligometastatic prostate adenocarcinoma challenges traditional linear models of metastatic progression and clinical reliance on PSA as a marker for PCa detection and treatment in advanced cases. By investigating key questions regarding the identity, timing, and trajectory of DTCs, we propose a biologically informed narrative of this patient’s disease progression and a reconsideration of metastases directed therapy (MDT) of oligometastases as primary therapy in select patients. Full article

Background: Accurate staging is vital for optimizing outcomes in pediatric rhabdomyosarcoma (RMS). While [¹⁸F]-FDG PET/CT is increasingly utilized, its specific impact on clinical management and its prognostic value compared to conventional imaging (CI) require further evaluation. Methods: In this retrospective single-center study, we reviewed 56 pediatric patients with RMS who underwent [¹⁸F]-FDG PET/CT at our center. Imaging findings were compared with CI (CT/MRI) and correlated with clinical management and survival outcomes. Results: In the total cohort (n = 56), PET/CT demonstrated high concordance with CI for nodal assessment, with an apparent sensitivity of 89.5% and specificity of 94.6%. PET/CT identified skeletal metastases in 5 patients (8.9%) and correctly characterized suspicious pulmonary nodules in one case, though it failed to detect a 0.6 cm lung nodule visualized on chest CT. Notably, PET/CT findings directly altered clinical management in 16.1% of patients (n = 9), primarily through radiotherapy adjustments, including field expansions (n = 4), field reductions (n = 3), and the initiation of previously unplanned radiotherapy (n = 2). At a median follow-up of 33.3 months, an exploratory analysis showed that patients with an SUVmax ≥3.6 had a lower 3-year EFS (57.6% vs. 71.6%; p = 0.51) and OS (60.4% vs. 71.6%; p = 0.63); neither comparison reached statistical significance. Conclusion: [¹⁸F]-FDG PET/CT is a powerful adjunct in pediatric RMS staging, particularly for nodal and skeletal evaluation. Its ability to refine radiotherapy planning in nearly one-sixth of cases underscores its clinical utility. SUVmax is not a validated prognostic or predictive biomarker in pediatric RMS; prospective, adequately powered multicenter studies, ideally incorporating volumetric PET parameters, are needed before any role in risk-stratified therapy can be defined. Full article